Bernhard Schölkopf

Yuen Chen

Nur Muhammad (Mahi) Shafiullah

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

[BibT_eX]

[DOI]

Henrik I. Christensen

Keerthana Gopalakrishnan

Lawrence Yunliang Chen

Roberto Martín-Martín

Subramanian Ramamoorthy

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Detecting and Identifying Selection Structure in Sequential Data.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Geometry-Aware Instrumental Variable Regression.

[BibT_eX]

[DOI]

Heiner Kremer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Provable Privacy with Non-Private Pre-Processing.

[BibT_eX]

[DOI]

Yaxi Hu

Amartya Sanyal

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Robustness of Nonlinear Representation Learning.

[BibT_eX]

[DOI]

Simon Buchholz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Identifying Policy Gradient Subspaces.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Skill or Luck? Return Decomposition via Advantage Functions.

[BibT_eX]

[DOI]

Hsiao-Ru Pan

Jonas Bernhard Wildberger

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Ghost on the Shell: An Expressive Representation of General 3D Shapes.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Can Large Language Models Infer Causation from Correlation?

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Out-of-Variable Generalisation for Discriminative Models.

[BibT_eX]

[DOI]

Siyuan Guo

Adithya Kumar Chinnakkonda Ravi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Diffusion-based learning of contact plans for agile locomotion.

[BibT_eX]

[DOI]

Victor Dhédin

Proceedings of the 23rd IEEE-RAS International Conference on Humanoid Robots, 2024

Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis.

[BibT_eX]

[DOI]

Zhiheng Lyu

Rada Mihalcea

Mrinmaya Sachan

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Implicit Personalization in Language Models: A Systematic Study.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Causal Modeling with Stationary Diffusions.

[BibT_eX]

[DOI]

Lars Lorch

Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Moûsai: Efficient Text-to-Music Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

CausalCite: A Causal Formulation of Paper Citations.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Kernel-Based Independence Tests for Causal Structure Learning on Functional Data.

[BibT_eX]

[DOI]

Entropy, December, 2023

Reinforcement learning with model-based feedforward inputs for robotic table tennis.

[BibT_eX]

[DOI]

Auton. Robots, December, 2023

normflows: A PyTorch Package for Normalizing Flows.

[BibT_eX]

[DOI]

Dataset, November, 2023

normflows: A PyTorch Package for Normalizing Flows.

[BibT_eX]

[DOI]

J. Open Source Softw., July, 2023

normflows: A PyTorch Package for Normalizing Flows.

[BibT_eX]

[DOI]

Dataset, July, 2023

Evaluating vaccine allocation strategies using simulation-assisted causal modeling.

[BibT_eX]

[DOI]

Patterns, June, 2023

normflows: A PyTorch Package for Normalizing Flows.

[BibT_eX]

[DOI]

Dataset, June, 2023

normflows: A PyTorch Package for Normalizing Flows.

[BibT_eX]

[DOI]

Dataset, June, 2023

nl-causal-representations.

[BibT_eX]

[DOI]

Dataset, April, 2023

Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases.

[BibT_eX]

[DOI]

PLoS Comput. Biol., January, 2023

Jacobian-based Causal Discovery with Nonlinear ICA.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Variational Causal Dynamics: Discovering Modular World Models from Interventions.

[BibT_eX]

[DOI]

Anson Lei

Ingmar Posner

Trans. Mach. Learn. Res., 2023

Neural Causal Structure Discovery from Interventions.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning.

[BibT_eX]

[DOI]

Nicholas D. Youngblut

PLoS Comput. Biol., 2023

A machine learning route between band mapping and band structure.

[BibT_eX]

[DOI]

Nat. Comput. Sci., 2023

Metrizing Weak Convergence with Maximum Mean Discrepancies.

[BibT_eX]

[DOI]

Alessandro Barp

Lester Mackey

J. Mach. Learn. Res., 2023

A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2023

Independent Mechanism Analysis and the Manifold Hypothesis.

[BibT_eX]

[DOI]

CoRR, 2023

Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling.

[BibT_eX]

[DOI]

CoRR, 2023

Targeted Reduction of Causal Models.

[BibT_eX]

[DOI]

Armin Kekic

CoRR, 2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations.

[BibT_eX]

[DOI]

CoRR, 2023

Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures.

[BibT_eX]

[DOI]

CoRR, 2023

CausalCite: A Causal Formulation of Paper Citations.

[BibT_eX]

[DOI]

CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

[BibT_eX]

[DOI]

CoRR, 2023

Borges and AI.

[BibT_eX]

[DOI]

Léon Bottou

CoRR, 2023

Investigating the Impact of Action Representations in Policy Gradient Algorithms.

[BibT_eX]

[DOI]

CoRR, 2023

Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks.

[BibT_eX]

[DOI]

CoRR, 2023

A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions.

[BibT_eX]

[DOI]

CoRR, 2023

The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks.

[BibT_eX]

[DOI]

CoRR, 2023

Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80.

[BibT_eX]

[DOI]

CoRR, 2023

Voices of Her: Analyzing Gender Differences in the AI Publication World.

[BibT_eX]

[DOI]

CoRR, 2023

All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations.

[BibT_eX]

[DOI]

CoRR, 2023

Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good.

[BibT_eX]

[DOI]

CoRR, 2023

Psychologically-Inspired Causal Prompts.

[BibT_eX]

[DOI]

CoRR, 2023

Out-of-Variable Generalization.

[BibT_eX]

[DOI]

Siyuan Guo

Jonas Wildberger

CoRR, 2023

Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Posterior Annealing: Fast Calibrated Uncertainty for Regression.

[BibT_eX]

[DOI]

CoRR, 2023

The passive symmetries of machine learning.

[BibT_eX]

[DOI]

CoRR, 2023

Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion.

[BibT_eX]

[DOI]

Flavio Schneider

CoRR, 2023

Causal effect estimation from observational and interventional data through matrix weighted linear estimators.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Hindsight States: Blending Sim & Real Task Elements for Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Flow Matching for Scalable Simulation-Based Inference.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Controlling Text-to-Image Diffusion by Orthogonal Finetuning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Measure-Theoretic Axiomatisation of Causality.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SE(3) Equivariant Augmented Coupling Flows.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Component Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Nonparametric Identifiability of Causal Representations from Unknown Interventions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models.

[BibT_eX]

[DOI]

Max Kleiman-Weiner

Mrinmaya Sachan

Marin Vlastelica Pogancic

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Leveraging sparse and shared feature activations for disentangled representation learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features.

[BibT_eX]

[DOI]

Cian Eastwood

Shashank Singh

Andrei Liviu Nicolicioiu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Locomotion Skills from MPC in Sensor Space.

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2023

Data-Efficient Online Learning of Ball Placement in Robot Table Tennis.

[BibT_eX]

[DOI]

IROS, 2023

AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Discrete Key-Value Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

The Hessian perspective into the Nature of Convolutional Neural Networks.

[BibT_eX]

[DOI]

Sidak Pal Singh

Thomas Hofmann

Tycho F. A. van der Ouderaa

Proceedings of the International Conference on Machine Learning, 2023

Diffusion Based Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Estimation Beyond Data Reweighting: Kernel Method of Moments.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

On the Relationship Between Explanation and Prediction: A Causal View.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

On the Identifiability and Estimation of Causal Location-Scale Noise Models.

[BibT_eX]

[DOI]

Alexander Immer

Christoph Schultheiss

Proceedings of the International Conference on Machine Learning, 2023

Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels.

[BibT_eX]

[DOI]

Alexander Immer

Mark van der Wilk

Proceedings of the International Conference on Machine Learning, 2023

On Data Manifolds Entailed by Structural Causal Models.

[BibT_eX]

[DOI]

Ricardo Dominguez-Olmedo

Proceedings of the International Conference on Machine Learning, 2023

Provably Learning Object-Centric Representations.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Bridging the Gap to Real-World Object-Centric Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Flow Annealed Importance Sampling Bootstrap.

[BibT_eX]

[DOI]

Laurence Illing Midgley

Vincent Stimper

Gregor N. C. Simm

Max-Olivier Van Bastelaer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Structure by Architecture: Structured Representations without Regularization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Benchmarking Offline Reinforcement Learning on Real-Robot Hardware.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability.

[BibT_eX]

[DOI]

Cian Eastwood

Andrei Liviu Nicolicioiu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Pairwise Similarity Learning is SimPLE.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Glare Removal for Astronomical Images with High Local Dynamic Range.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computational Photography, 2023

Robustness Implies Fairness in Causal Algorithmic Recourse.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good.

[BibT_eX]

[DOI]

Jonas Bernhard Wildberger

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

On the Interventional Kullback-Leibler Divergence.

[BibT_eX]

[DOI]

Siyuan Guo

Arnab Bhattacharyya

Fatemehsadat Mireshghallah

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Unsupervised Object Learning via Common Fate.

[BibT_eX]

[DOI]

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Dataflow graphs as complete causal graphs.

[BibT_eX]

[DOI]

Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

Iterative Teaching by Data Hallucination.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

BaCaDI: Bayesian Causal Discovery with Unknown Interventions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models.

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Membership Inference Attacks against Language Models via Neighbourhood Comparison.

[BibT_eX]

[DOI]

Justus Mattern

Mrinmaya Sachan

Taylor Berg-Kirkpatrick

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

nl-causal-representations.

[BibT_eX]

[DOI]

Dataset, August, 2022

ima-vae.

[BibT_eX]

[DOI]

Dataset, June, 2022

Age-stratified Covid-19 case fatality rates (CFRs): different countries and longitudinal.

[BibT_eX]

[DOI]

Luigi Gresele

Dataset, May, 2022

Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots.

[BibT_eX]

[DOI]

ACM Trans. Spatial Algorithms Syst., 2022

Learning to Play Table Tennis From Scratch Using Muscular Robots.

[BibT_eX]

[DOI]

IEEE Trans. Robotics, 2022

Causal Feature Selection via Orthogonal Search.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2022

Understanding Stereotypes in Language Models: Towards Robust Measurement and Zero-Shot Debiasing.

[BibT_eX]

[DOI]

CoRR, 2022

Evaluating vaccine allocation strategies using simulation-assisted causal modelling.

[BibT_eX]

[DOI]

CoRR, 2022

Adapting to noise distribution shifts in flow-based gravitational-wave inference.

[BibT_eX]

[DOI]

CoRR, 2022

FED-CD: Federated Causal Discovery from Interventional and Observational Data.

[BibT_eX]

[DOI]

CoRR, 2022

A General Purpose Neural Architecture for Geospatial Systems.

[BibT_eX]

[DOI]

CoRR, 2022

Spectral Representation Learning for Conditional Moment Models.

[BibT_eX]

[DOI]

CoRR, 2022

AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference.

[BibT_eX]

[DOI]

CoRR, 2022

When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment.

[BibT_eX]

[DOI]

CoRR, 2022

Probing the Robustness of Independent Mechanism Analysis for Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework.

[BibT_eX]

[DOI]

CoRR, 2022

From Statistical to Causal Learning.

[BibT_eX]

[DOI]

CoRR, 2022

On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective".

[BibT_eX]

[DOI]

CoRR, 2022

Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Physical Derivatives: Computing policy gradients by physical forward-propagation.

[BibT_eX]

[DOI]

CoRR, 2022

Learning soft interventions in complex equilibrium systems.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Assaying Out-Of-Distribution Generalization in Transfer Learning.

[BibT_eX]

[DOI]

Florian Wenzel

Andrea Dittadi

Peter V. Gehler

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural Attentive Circuits.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Interventions, Where and How? Experimental Design for Causal Models at Scale.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Embrace the Gap: VAEs Perform Independent Mechanism Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis.

[BibT_eX]

[DOI]

Ronan Perry

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Direct Advantage Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Amortized Inference for Causal Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploring the Latent Space of Autoencoders with Interventional Assays.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

AutoML Two-Sample Test.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment.

[BibT_eX]

[DOI]

Sydney Levine

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Probable Domain Generalization via Quantile Risk Minimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization.

[BibT_eX]

[DOI]

Aniket Das

Michael Muehlebach

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Function Classes for Identifiable Nonlinear Independent Component Analysis.

[BibT_eX]

[DOI]

Simon Buchholz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance.

[BibT_eX]

[DOI]

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models.

[BibT_eX]

[DOI]

Paul Rolland

Volkan Cevher

Matthäus Kleindessner

Proceedings of the International Conference on Machine Learning, 2022

Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Action-Sufficient State Representation Learning for Control with Structural Constraints.

[BibT_eX]

[DOI]

Biwei Huang

Liu Leqi

Clark Glymour

Proceedings of the International Conference on Machine Learning, 2022

Causal Inference Through the Structural Causal Marginal Problem.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

On the Adversarial Robustness of Causal Algorithmic Recourse.

[BibT_eX]

[DOI]

Ricardo Dominguez-Olmedo

Proceedings of the International Conference on Machine Learning, 2022

Generalization and Robustness Implications in Object-Centric Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Adversarial Robustness Through the Lens of Causality.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

The Role of Pretrained Representations for the OOD Generalization of RL Agents.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Phenomenology of Double Descent in Finite-Width Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Invariant Causal Representation Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Yuhuai Wu

Christopher K. I. Williams

Proceedings of the Tenth International Conference on Learning Representations, 2022

Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration.

[BibT_eX]

[DOI]

Cian Eastwood

Ian Mason

Proceedings of the Tenth International Conference on Learning Representations, 2022

Group equivariant neural posterior estimation.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Differentially Private Language Models for Secure Data Sharing.

[BibT_eX]

[DOI]

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Logical Fallacy Detection.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Structural Causal 3D Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers.

[BibT_eX]

[DOI]

Dominik Zietlow

Michael Lohaus

Guha Balakrishnan

Matthäus Kleindessner

Chris Russell

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Principled Disentanglement for Domain Generalization.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Total Recall in Industrial Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations.

[BibT_eX]

[DOI]

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Learning Random Feature Dynamics for Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Adversarially Robust Kernel Smoothing.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Resampling Base Distributions of Normalizing Flows.

[BibT_eX]

[DOI]

Vincent Stimper

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

A Witness Two-Sample Test.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

A prior-based approximate latent Riemannian metric.

[BibT_eX]

[DOI]

Bogdan M. Georgiev

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On the Fairness of Causal Algorithmic Recourse.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Causality for Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021

ArmSym: A Virtual Human-Robot Interaction Laboratory for Assistive Robotics.

[BibT_eX]

[DOI]

Samuel Bustamante

Vinay Jayaram

IEEE Trans. Hum. Mach. Syst., 2021

Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects.

[BibT_eX]

[DOI]

Luigi Gresele

IEEE Trans. Artif. Intell., 2021

Toward Causal Representation Learning.

[BibT_eX]

[DOI]

Proc. IEEE, 2021

Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control.

[BibT_eX]

[DOI]

CoRR, 2021

Boxhead: A Dataset for Learning Hierarchical Representations.

[BibT_eX]

[DOI]

CoRR, 2021

A Robot Cluster for Reproducible Research in Dexterous Manipulation.

[BibT_eX]

[DOI]

CoRR, 2021

Learning Neural Causal Models with Active Interventions.

[BibT_eX]

[DOI]

CoRR, 2021

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Interventional Assays for the Latent Space of Autoencoders.

[BibT_eX]

[DOI]

Felix Leeb

CoRR, 2021

Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics.

[BibT_eX]

[DOI]

CoRR, 2021

Real-time gravitational-wave science with neural posterior estimation.

[BibT_eX]

[DOI]

CoRR, 2021

Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects.

[BibT_eX]

[DOI]

CoRR, 2021

Instrument Space Selection for Kernel Maximum Moment Restriction.

[BibT_eX]

[DOI]

CoRR, 2021

Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases.

[BibT_eX]

[DOI]

CoRR, 2021

A prior-based approximate latent Riemannian metric.

[BibT_eX]

[DOI]

Bogdan Georgiev

CoRR, 2021

Nonlinear Invariant Risk Minimization: A Causal Approach.

[BibT_eX]

[DOI]

Yuhuai Wu

CoRR, 2021

Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners.

[BibT_eX]

[DOI]

Maximilian Mordig

Riccardo Della Vecchia

Nicolò Cesa-Bianchi

CoRR, 2021

Towards Causal Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2021

From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing.

[BibT_eX]

[DOI]

CoRR, 2021

An Optimal Witness Function for Two-Sample Testing.

[BibT_eX]

[DOI]

CoRR, 2021

Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2021

Regret Bounds for Gaussian-Process Optimization in Large Domains.

[BibT_eX]

[DOI]

Manuel Wüthrich

Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Backward-Compatible Prediction Updates: A Probabilistic Approach.

[BibT_eX]

[DOI]

Frederik Träuble

Matthäus Kleindessner

Peter V. Gehler

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Causal Influence Detection for Improving Efficiency in Reinforcement Learning.

[BibT_eX]

[DOI]

Maximilian Seitzer

Georg Martius

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Inference with Neural Interpreters.

[BibT_eX]

[DOI]

Nasim Rahaman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DiBS: Differentiable Bayesian Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Iterative Teaching by Label Synthesis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Inductive Bias of Quantum Kernels.

[BibT_eX]

[DOI]

Jonas M. Kübler

Simon Buchholz

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2022 Competition Track, 2021

Independent mechanism analysis, a new concept?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Real Robot Challenge: A Robotics Competition in the Cloud.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Neural Lyapunov Redesign.

[BibT_eX]

[DOI]

Mohammad Ghavamzadeh

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

On Disentangled Representations Learned from Correlated Data.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Necessary and sufficient conditions for causal feature selection in time series with latent common causes.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Function Contrastive Learning of Transferable Meta-Representations.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Bayesian Quadrature on Riemannian Data Manifolds.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Spatially Structured Recurrent Modules.

[BibT_eX]

[DOI]

Nasim Rahaman

Anirudh Goyal

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning explanations that are hard to vary.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

A teacher-student framework to distill future trajectories.

[BibT_eX]

[DOI]

Alexander Neitz

Proceedings of the 9th International Conference on Learning Representations, 2021

Fast And Slow Learning Of Recurrent Independent Mechanisms.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Recurrent Independent Mechanisms.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

On the Transfer of Disentangled Representations in Realistic Settings.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Predicting Infectiousness for Proactive Contact Tracing.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Algorithmic Recourse: from Counterfactual Explanations to Interventions.

[BibT_eX]

[DOI]

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP.

[BibT_eX]

[DOI]

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning with Hyperspherical Uniformity.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Geometrically Enriched Latent Spaces.

[BibT_eX]

[DOI]

Søren Hauberg

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Theory of Independent Mechanisms for Extrapolation in Generative Models.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adaptation and Robust Learning of Probabilistic Movement Primitives.

[BibT_eX]

[DOI]

Gerhard Neumann

IEEE Trans. Robotics, 2020

Real Time Trajectory Prediction Using Deep Conditional Generative Models.

[BibT_eX]

[DOI]

Sergey Prokudin

IEEE Robotics Autom. Lett., 2020

A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Causal Discovery from Heterogeneous/Nonstationary Data.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation.

[BibT_eX]

[DOI]

Biwei Huang

Ke Wang

CoRR, 2020

PanCast: Listening to Bluetooth Beacons for Epidemic Risk Mitigation.

[BibT_eX]

[DOI]

CoRR, 2020

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.

[BibT_eX]

[DOI]

CoRR, 2020

Maximum Moment Restriction for Instrumental Variable Regression.

[BibT_eX]

[DOI]

CoRR, 2020

Function Contrastive Learning of Transferable Representations.

[BibT_eX]

[DOI]

CoRR, 2020

Physically constrained causal noise models for high-contrast imaging of exoplanets.

[BibT_eX]

[DOI]

CoRR, 2020

A survey of algorithmic recourse: definitions, formulations, solutions, and prospects.

[BibT_eX]

[DOI]

CoRR, 2020

Real-time Prediction of COVID-19 related Mortality using Electronic Health Records.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Dynamical Systems using Local Stability Priors.

[BibT_eX]

[DOI]

Andrea Iannelli

CoRR, 2020

TriFinger: An Open-Source Robot for Learning Dexterity.

[BibT_eX]

[DOI]

CoRR, 2020

Bloom Origami Assays: Practical Group Testing.

[BibT_eX]

[DOI]

Anshumali Shrivastava

CoRR, 2020

S2RMs: Spatially Structured Recurrent Modules.

[BibT_eX]

[DOI]

Nasim Rahaman

Anirudh Goyal

CoRR, 2020

Is Independence all you need? On the Generalization of Representations Learned from Correlated Data.

[BibT_eX]

[DOI]

CoRR, 2020

Structural Autoencoders Improve Representations for Generation and Transfer.

[BibT_eX]

[DOI]

CoRR, 2020

Kernel Distributionally Robust Optimization.

[BibT_eX]

[DOI]

CoRR, 2020

Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems.

[BibT_eX]

[DOI]

Mohammad Ghavamzadeh

CoRR, 2020

Crackovid: Optimizing Group Testing.

[BibT_eX]

[DOI]

Louis Abraham

Gary Bécigneul

CoRR, 2020

Towards causal generative scene models via competition of experts.

[BibT_eX]

[DOI]

CoRR, 2020

A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment.

[BibT_eX]

[DOI]

CoRR, 2020

SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives.

[BibT_eX]

[DOI]

CoRR, 2020

DeepMAsED: evaluating the quality of metagenomic assemblies.

[BibT_eX]

[DOI]

Nicholas D. Youngblut

Bioinform., 2020

MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware.

[BibT_eX]

[DOI]

Proceedings of the UIST '20: The 33rd Annual ACM Symposium on User Interface Software and Technology, 2020

On the design of consequential ranking algorithms.

[BibT_eX]

[DOI]

Manuel Gomez Rodriguez

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Semi-supervised learning, causality, and the conditional cluster assumption.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Testing Goodness of Fit of Conditional Density Models with Kernels.

[BibT_eX]

[DOI]

Wittawat Jitkrittum

Heishiro Kanagawa

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Bayesian Online Prediction of Change Points.

[BibT_eX]

[DOI]

Diego Agudelo-España

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Causal analysis of Covid-19 Spread in Germany.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Kernel Tests Without Data Splitting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Algorithmic recourse under imperfect causal knowledge: a probabilistic approach.

[BibT_eX]

[DOI]

Bodo Julius von Kügelgen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Relative gradient optimization of the Jacobian term in unsupervised deep learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control.

[BibT_eX]

[DOI]

Moritz Diehl

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Weakly-Supervised Disentanglement Without Compromises.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Towards Causal Algorithmic Recourse.

[BibT_eX]

[DOI]

Proceedings of the xxAI - Beyond Explainable AI, 2020

Disentangling Factors of Variations Using Few Labels.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

From Variational to Deterministic Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Counterfactuals uncover the modular structure of deep generative models.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

TriFinger: An Open-Source Robot for Learning Dexterity.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Robot Learning, 2020

Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Fair Decisions Despite Imperfect Predictions.

[BibT_eX]

[DOI]

Manuel Gomez Rodriguez

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Commentary on the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Reliable Real-Time Ball Tracking for Robot Table Tennis.

[BibT_eX]

[DOI]

Robotics, 2019

Analysis of cause-effect inference by comparing regression errors.

[BibT_eX]

[DOI]

PeerJ Comput. Sci., 2019

Data scarcity, robustness and extreme multi-label classification.

[BibT_eX]

[DOI]

Mach. Learn., 2019

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2019

A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming.

[BibT_eX]

[DOI]

CoRR, 2019

Causality for Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks.

[BibT_eX]

[DOI]

CoRR, 2019

Disentangled State Space Representations.

[BibT_eX]

[DOI]

Ðorðe Miladinovic

Joachim M. Buhmann

CoRR, 2019

Quantum Mean Embedding of Probability Distributions.

[BibT_eX]

[DOI]

Jonas M. Kübler

CoRR, 2019

Optimal Decision Making Under Strategic Behavior.

[BibT_eX]

[DOI]

CoRR, 2019

Consequential Ranking Algorithms and Long-term Welfare.

[BibT_eX]

[DOI]

Manuel Gomez Rodriguez

CoRR, 2019

Disentangling Factors of Variation Using Few Labels.

[BibT_eX]

[DOI]

CoRR, 2019

Convolutional neural networks: a magic bullet for gravitational-wave detection?

[BibT_eX]

[DOI]

CoRR, 2019

Bayesian Online Detection and Prediction of Change Points.

[BibT_eX]

[DOI]

Diego Agudelo-España

CoRR, 2019

Improving Consequential Decision Making under Imperfect Predictions.

[BibT_eX]

[DOI]

CoRR, 2019

GeNet: Deep Representations for Metagenomics.

[BibT_eX]

[DOI]

Guillermo Luque

Nicholas D. Youngblut

Ruth E. Ley

CoRR, 2019

Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces.

[BibT_eX]

[DOI]

CoRR, 2019

Multidimensional Contrast Limited Adaptive Histogram Equalization.

[BibT_eX]

[DOI]

IEEE Access, 2019

The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Neural Signatures of Motor Skill in the Resting Brain.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Perceiving the arrow of time in autoregressive motion.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Selecting causal brain features with a single conditional independence test per feature.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Fairness of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Kernel Stein Tests for Multiple Model Comparison.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Feature extraction from the Hermitian manifold for Brain-Computer Interfaces.

[BibT_eX]

[DOI]

Jiachen Xu

Vinay Jayaram

Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

First-Order Adversarial Vulnerability of Neural Networks and Input Dimension.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Kernel Mean Matching for Content Addressability of GANs.

[BibT_eX]

[DOI]

Wittawat Jitkrittum

Patsorn Sangkloy

Amit Raj

James Hays

Proceedings of the 36th International Conference on Machine Learning, 2019

AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments.

[BibT_eX]

[DOI]

Ðorðe Miladinovic

Joachim M. Buhmann

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Learning causal mechanisms.

[BibT_eX]

[DOI]

Proceedings of the 49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik, 2019

Beta Power May Meditate the Effect of Gamma-TACS on Motor Performance.

[BibT_eX]

[DOI]

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

MYND: A Platform for Large-scale Neuroscientific Studies.

[BibT_eX]

[DOI]

Proceedings of the Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

2018

Discriminative Transfer Learning for General Image Restoration.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2018

Control of Musculoskeletal Systems Using Learned Dynamics Models.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2018

Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2018

Invariant Models for Causal Transfer Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2018

Deconfounding Reinforcement Learning in Observational Settings.

[BibT_eX]

[DOI]

CoRR, 2018

Counterfactuals uncover the modular structure of deep generative models.

[BibT_eX]

[DOI]

Rémy Sun

CoRR, 2018

Generalization in anti-causal learning.

[BibT_eX]

[DOI]

CoRR, 2018

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Nonlinear Non-Gaussian Filtering for Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Interventional Robustness of Deep Latent Variable Models.

[BibT_eX]

[DOI]

CoRR, 2018

Photorealistic Video Super Resolution.

[BibT_eX]

[DOI]

Eduardo Pérez-Pellitero

CoRR, 2018

groupICA: Independent component analysis for grouped data.

[BibT_eX]

[DOI]

CoRR, 2018

A Local Information Criterion for Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Minimum Information Exchange in Distributed Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Energy Estimator Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Revisiting First-Order Convex Optimization Over Linear Spaces.

[BibT_eX]

[DOI]

Anant Raj

Sai Praneeth Karimireddy

CoRR, 2018

Coordination via predictive assistants from a game-theoretic view.

[BibT_eX]

[DOI]

CoRR, 2018

Adversarial Extreme Multi-label Classification.

[BibT_eX]

[DOI]

CoRR, 2018

Analysis of Cause-Effect Inference via Regression Errors.

[BibT_eX]

[DOI]

CoRR, 2018

Tempered Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2018

On the Latent Space of Wasserstein Auto-Encoders.

[BibT_eX]

[DOI]

Paul K. Rubenstein

CoRR, 2018

Adversarial Vulnerability of Neural Networks Increases With Input Dimension.

[BibT_eX]

[DOI]

CoRR, 2018

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation.

[BibT_eX]

[DOI]

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

From Deterministic ODEs to Dynamic Structural Causal Models.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models.

[BibT_eX]

[DOI]

Alexander Neitz

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Informative Features for Model Comparison.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalized Score Functions for Causal Discovery.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Tempered Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Independent Causal Mechanisms.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

On Matching Pursuit and Coordinate Descent.

[BibT_eX]

[DOI]

Anant Raj

Sai Praneeth Karimireddy

Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting non-causal artifacts in multivariate linear regression models.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Differentially Private Database Release via Kernel Mean Embeddings.

[BibT_eX]

[DOI]

Matej Balog

Proceedings of the 35th International Conference on Machine Learning, 2018

Wasserstein Auto-Encoders.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders.

[BibT_eX]

[DOI]

Paul K. Rubenstein

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Disentangled Representations with Wasserstein Auto-Encoders.

[BibT_eX]

[DOI]

Paul K. Rubenstein

Proceedings of the 6th International Conference on Learning Representations, 2018

Clustering Meets Implicit Generative Models.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Fidelity-Weighted Learning.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Automatic estimation of modulation transfer functions.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Computational Photography, 2018

Spatio-Temporal Transformer Network for Video Restoration.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Efficient Encoding of Dynamical Systems Through Local Approximations.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Cause-Effect Inference by Comparing Regression Errors.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Group invariance principles for causal generative models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

BundleMAP: Anatomically localized classification, regression, and hypothesis testing in diffusion MRI.

[BibT_eX]

[DOI]

Mohammad Khatami

Tobias Schmidt-Wilcke

Pattern Recognit., 2017

Kernel Mean Embedding of Distributions: A Review and Beyond.

[BibT_eX]

[DOI]

Found. Trends Mach. Learn., 2017

Optimizing Human Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Probabilistic Active Learning of Functions in Structural Causal Models.

[BibT_eX]

[DOI]

CoRR, 2017

Annealed Generative Adversarial Networks.

[BibT_eX]

[DOI]

Saeed Saremi

CoRR, 2017

Discriminative k-shot learning using probabilistic models.

[BibT_eX]

[DOI]

Matthias Bauer

Jakub Bartlomiej Swiatkowski

Richard E. Turner

CoRR, 2017

Anticipatory action selection for human-robot table tennis.

[BibT_eX]

[DOI]

Artif. Intell., 2017

Distilling Information Reliability and Source Trustworthiness from Digital Traces.

[BibT_eX]

[DOI]

Proceedings of the 26th International Conference on World Wide Web, 2017

DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification.

[BibT_eX]

[DOI]

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Causal Consistency of Structural Equation Models.

[BibT_eX]

[DOI]

Anastasia-Atalanti Mastakouri

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Causal Discovery from Temporally Aggregated Time Series.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Personalized brain-computer interface models for motor rehabilitation.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

AdaGAN: Boosting Generative Models.

[BibT_eX]

[DOI]

Sylvain Gelly

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Avoiding Discrimination through Causal Reasoning.

[BibT_eX]

[DOI]

Moritz Hardt

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Frequency peak features for low-channel classification in motor imagery paradigms.

[BibT_eX]

[DOI]

Vinay Jayaram

Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Learning Blind Motion Deblurring.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Online Video Deblurring via Dynamic Temporal Blending Network.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

A Guided Task for Cognitive brain-Computer Interfaces.

[BibT_eX]

[DOI]

Julia Moser

Matthias Hohmann

Proceedings of the From Vision to Reality, 2017

Closing One's eyes Affects amplitude modulation but not frequency modulation in a Cognitive BCI.

[BibT_eX]

[DOI]

Marius Goerner

Proceedings of the From Vision to Reality, 2017

Flexible Spatio-Temporal Networks for Video Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Discovering Causal Signals in Images.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Local Group Invariant Representations via Orbit Embeddings.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Influence Estimation and Maximization in Continuous-Time Diffusion Networks.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., 2016

On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2016

Preface to the ACM TIST Special Issue on Causal Discovery and Inference.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2016

Gaussian Process-Based Predictive Control for Periodic Error Correction.

[BibT_eX]

[DOI]

Edgar D. Klenske

Melanie Nicole Zeilinger

IEEE Trans. Control. Syst. Technol., 2016

Modeling confounding by half-sibling regression.

[BibT_eX]

[DOI]

David W. Hogg

Dun Wang

Daniel Foreman-Mackey

Proc. Natl. Acad. Sci. USA, 2016

Learning to Deblur.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach.

[BibT_eX]

[DOI]

Markus Siegel

NeuroImage, 2016

Kernel Mean Shrinkage Estimators.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm.

[BibT_eX]

[DOI]

Le Song

Hadi Daneshmand

J. Mach. Learn. Res., 2016

New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481).

[BibT_eX]

[DOI]

Dagstuhl Reports, 2016

Optimal Coding in Biological and Artificial Neural Networks.

[BibT_eX]

[DOI]

Sebastian Weichwald

Tatiana Fomina

CoRR, 2016

Screening Rules for Convex Problems.

[BibT_eX]

[DOI]

CoRR, 2016

Kernel Mean Embedding of Distributions: A Review and Beyonds.

[BibT_eX]

[DOI]

CoRR, 2016

Unifying distillation and privileged information.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Experimental and causal view on information integration in autonomous agents.

[BibT_eX]

[DOI]

Philipp Geiger

Katja Hofmann

CoRR, 2016

Causal models for debugging and control in cloud computing.

[BibT_eX]

[DOI]

Philipp Geiger

Lucian Carata

CoRR, 2016

Structural Causal Models: Cycles, Marginalizations, Exogenous Reparametrizations and Reductions.

[BibT_eX]

[DOI]

CoRR, 2016

Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail.

[BibT_eX]

[DOI]

IEEE Comput. Intell. Mag., 2016

On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data.

[BibT_eX]

[DOI]

Sebastian Weichwald

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Consistent Kernel Mean Estimation for Functions of Random Variables.

[BibT_eX]

[DOI]

Adam Scibior

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Domain Adaptation with Conditional Transferable Components.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

The Arrow of Time in Multivariate Time Series.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Jointly learning trajectory generation and hitting point prediction in robot table tennis.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Using probabilistic movement primitives for striking movements.

[BibT_eX]

[DOI]

Gerhard Neumann

Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Approximate dual control maintaining the value of information with an application to building control.

[BibT_eX]

[DOI]

Edgar D. Klenske

Melanie Nicole Zeilinger

Proceedings of the 15th European Control Conference, 2016

Depth Estimation Through a Generative Model of Light Field Synthesis.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 38th German Conference, 2016

End-to-End Learning for Image Burst Deblurring.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

Computing functions of random variables via reproducing kernel Hilbert space representations.

[BibT_eX]

[DOI]

Stat. Comput., 2015

Causal interpretation rules for encoding and decoding models in neuroimaging.

[BibT_eX]

[DOI]

NeuroImage, 2015

Artificial intelligence: Learning to see and act.

[BibT_eX]

[DOI]

Nat., 2015

Semi-supervised interpolation in an anticausal learning scenario.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2015

Distinguishing Cause from Effect Based on Exogeneity.

[BibT_eX]

[DOI]

Jiji Zhang

CoRR, 2015

Towards Robust and Specific Causal Discovery from fMRI.

[BibT_eX]

[DOI]

CoRR, 2015

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations.

[BibT_eX]

[DOI]

CoRR, 2015

Transfer Learning in Brain-Computer Interfaces.

[BibT_eX]

[DOI]

Jennifer Muller vom Hagen

CoRR, 2015

A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis.

[BibT_eX]

[DOI]

Matthis Synofzik

Ludger Schöls

Proceedings of the 2015 IEEE International Conference on Systems, 2015

BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease.

[BibT_eX]

[DOI]

Mohammad Khatami

Tobias Schmidt-Wilcke

Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015

Learning optimal striking points for a ping-pong playing robot.

[BibT_eX]

[DOI]

Yanlong Huang

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Identification of Time-Dependent Causal Model: A Gaussian Process Treatment.

[BibT_eX]

[DOI]

Biwei Huang

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Telling cause from effect in deterministic linear dynamical systems.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Removing systematic errors for exoplanet search via latent causes.

[BibT_eX]

[DOI]

David W. Hogg

Dun Wang

Daniel Foreman-Mackey

Proceedings of the 32nd International Conference on Machine Learning, 2015

Towards a Learning Theory of Cause-Effect Inference.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Retrospective Motion Correction of Magnitude-Input MR Images.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning Meets Medical Imaging - First International Workshop, 2015

Discovering Temporal Causal Relations from Subsampled Data.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Self-Calibration of Optical Lenses.

[BibT_eX]

[DOI]

Jennifer Muller vom Hagen

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Brain-computer interfacing in amyotrophic lateral sclerosis: Implications of a resting-state EEG analysis.

[BibT_eX]

[DOI]

Matthis Synofzik

Ludger Schöls

Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Identification of the Default Mode Network with electroencephalography.

[BibT_eX]

[DOI]

Tatiana Fomina

Matthias Hohmann

Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Inference of Cause and Effect with Unsupervised Inverse Regression.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Multi-Source Domain Adaptation: A Causal View.

[BibT_eX]

[DOI]

Mingming Gong

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2014

Uncovering the structure and temporal dynamics of information propagation.

[BibT_eX]

[DOI]

Jure Leskovec

David Balduzzi

Netw. Sci., 2014

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings.

[BibT_eX]

[DOI]

Neural Comput., 2014

Causal discovery with continuous additive noise models.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2014

Learning strategies in table tennis using inverse reinforcement learning.

[BibT_eX]

[DOI]

Biol. Cybern., 2014

Estimating Causal Effects by Bounding Confounding.

[BibT_eX]

[DOI]

Philipp Geiger

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

A Permutation-Based Kernel Conditional Independence Test.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Inferring latent structures via information inequalities.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Causal and anti-causal learning in pattern recognition for neuroimaging.

[BibT_eX]

[DOI]

Sebastian Weichwald

Tonio Ball

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Kernel Mean Estimation via Spectral Filtering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Quantifying Information Overload in Social Media and Its Impact on Social Contagions.

[BibT_eX]

[DOI]

Krishna P. Gummadi

Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

Kernel Mean Estimation and Stein Effect.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Randomized Nonlinear Component Analysis.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Consistency of Causal Inference under the Additive Noise Model.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm.

[BibT_eX]

[DOI]

Hadi Daneshmand

Le Song

Proceedings of the 31th International Conference on Machine Learning, 2014

Mask-Specific Inpainting with Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 36th German Conference, 2014

Seeing the Arrow of Time.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem.

[BibT_eX]

[DOI]

Le Song

Proceedings of The 27th Conference on Learning Theory, 2014

Decoding index finger position from EEG using random forests.

[BibT_eX]

[DOI]

Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

Towards building a Crowd-Sourced Sky Map.

[BibT_eX]

[DOI]

Dustin Lang

David W. Hogg

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Probabilistic movement modeling for intention inference in human-robot interaction.

[BibT_eX]

[DOI]

Zhikun Wang

Katharina Mülling

Marc Peter Deisenroth

Int. J. Robotics Res., 2013

Kernel Mean Estimation and Stein's Effect.

[BibT_eX]

[DOI]

CoRR, 2013

HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization.

[BibT_eX]

[DOI]

Thomas Schultz

Lara Schlaffke

Tobias Schmidt-Wilcke

Comput. Graph. Forum, 2013

Structure and dynamics of information pathways in online media.

[BibT_eX]

[DOI]

Jure Leskovec

Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

One-Class Support Measure Machines for Group Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

From Ordinary Differential Equations to Structural Causal Models: the deterministic case.

[BibT_eX]

[DOI]

Joris M. Mooij

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data.

[BibT_eX]

[DOI]

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Causal Inference on Time Series using Restricted Structural Equation Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Randomized Dependence Coefficient.

[BibT_eX]

[DOI]

David López-Paz

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators.

[BibT_eX]

[DOI]

Nikos K. Logothetis

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Domain Adaptation under Target and Conditional Shift.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

Domain Generalization via Invariant Feature Representation.

[BibT_eX]

[DOI]

David Balduzzi

Proceedings of the 30th International Conference on Machine Learning, 2013

Modeling Information Propagation with Survival Theory.

[BibT_eX]

[DOI]

Jure Leskovec

Proceedings of the 30th International Conference on Machine Learning, 2013

Improving alpha matting and motion blurred foreground estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Image Processing, 2013

On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example.

[BibT_eX]

[DOI]

Zhikun Wang

Harold Christopher Burger

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

A Machine Learning Approach for Non-blind Image Deconvolution.

[BibT_eX]

[DOI]

Christian J. Schuler

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension.

[BibT_eX]

[DOI]

Yevgeny Seldin

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Semi-supervised Learning in Causal and Anticausal Settings.

[BibT_eX]

[DOI]

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Nonparametric dynamics estimation for time periodic systems.

[BibT_eX]

[DOI]

Edgar D. Klenske

Melanie Nicole Zeilinger

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

A Kernel Two-Sample Test.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

easyGWAS: An integrated interspecies platform for performing genome-wide association studies

[BibT_eX]

[DOI]

CoRR, 2012

Causal Inference on Time Series using Structural Equation Models

[BibT_eX]

[DOI]

CoRR, 2012

Information-geometric approach to inferring causal directions.

[BibT_eX]

[DOI]

Artif. Intell., 2012

Probabilistic Modeling of Human Movements for Intention Inference.

[BibT_eX]

[DOI]

Zhikun Wang

Marc Peter Deisenroth

Proceedings of the Robotics: Science and Systems VIII, 2012

Learning from Distributions via Support Measure Machines.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Semi-Supervised Domain Adaptation with Non-Parametric Copulas.

[BibT_eX]

[DOI]

David López-Paz

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The representer theorem for Hilbert spaces: a necessary and sufficient condition.

[BibT_eX]

[DOI]

Francesco Dinuzzo

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A brain-robot interface for studying motor learning after stroke.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

On causal and anticausal learning.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

Submodular Inference of Diffusion Networks from Multiple Trees.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

Influence Maximization in Continuous Time Diffusion Networks.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

A blind deconvolution approach for pseudo CT prediction from MR image pairs.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Blind Correction of Optical Aberrations.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2012, 2012

Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Statistical Learning Theory: Models, Concepts, and Results.

[BibT_eX]

[DOI]

Ulrike von Luxburg

Proceedings of the Inductive Logic, 2011

Causal Inference on Discrete Data Using Additive Noise Models.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Causal influence of gamma oscillations on the sensorimotor rhythm.

[BibT_eX]

[DOI]

N. Jeremy Hill

NeuroImage, 2011

A Graphical Model Framework for Decoding in the Visual ERP-Based BCI Speller.

[BibT_eX]

[DOI]

Neural Comput., 2011

Multi-way set enumeration in weight tensors.

[BibT_eX]

[DOI]

Elisabeth Georgii

Mach. Learn., 2011

A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps.

[BibT_eX]

[DOI]

Michael Habeck

J. Comput. Biol., 2011

Robust Learning via Cause-Effect Models

[BibT_eX]

[DOI]

CoRR, 2011

Kernel-based Conditional Independence Test and Application in Causal Discovery.

[BibT_eX]

[DOI]

Proceedings of the UAI 2011, 2011

Identifiability of Causal Graphs using Functional Models.

[BibT_eX]

[DOI]

Proceedings of the UAI 2011, 2011

Detecting low-complexity unobserved causes.

[BibT_eX]

[DOI]

Proceedings of the UAI 2011, 2011

On Causal Discovery with Cyclic Additive Noise Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Two-locus association mapping in subquadratic time.

[BibT_eX]

[DOI]

Panagiotis Achlioptas

Karsten M. Borgwardt

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Learning anticipation policies for robot table tennis.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Learning inverse kinematics with structured prediction.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Uncovering the Temporal Dynamics of Diffusion Networks.

[BibT_eX]

[DOI]

David Balduzzi

Proceedings of the 28th International Conference on Machine Learning, 2011

Support Vector Machines as Probabilistic Models.

[BibT_eX]

[DOI]

Vojtech Franc

Harold Christopher Burger

Proceedings of the 28th International Conference on Machine Learning, 2011

Non-stationary correction of optical aberrations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2011

Fast removal of non-uniform camera shake.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2011

Removing noise from astronomical images using a pixel-specific noise model.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE International Conference on Computational Photography, 2011

Finding dependencies between frequencies with the kernel cross-spectral density.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Causal inference using the algorithmic Markov condition.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2010

Nonparametric Regression between General Riemannian Manifolds.

[BibT_eX]

[DOI]

Matthias Hein

SIAM J. Imaging Sci., 2010

Remote Sensing Feature Selection by Kernel Dependence Measures.

[BibT_eX]

[DOI]

Gustavo Camps-Valls

Joris M. Mooij

IEEE Geosci. Remote. Sens. Lett., 2010

Hilbert Space Embeddings and Metrics on Probability Measures.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

Identifying Cause and Effect on Discrete Data using Additive Noise Models.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Causality: Objectives and Assessment.

[BibT_eX]

[DOI]

Isabelle Guyon

Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010

Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis.

[BibT_eX]

[DOI]

J. Comput. Neurosci., 2010

Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery.

[BibT_eX]

[DOI]

Proceedings of the UAI 2010, 2010

Inferring deterministic causal relations.

[BibT_eX]

[DOI]

Proceedings of the UAI 2010, 2010

Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Systems, 2010

A New Algorithm for Improving the Resolution of Cryo-EM Density Maps.

[BibT_eX]

[DOI]

Michael Habeck

Proceedings of the Research in Computational Molecular Biology, 2010

Probabilistic latent variable models for distinguishing between cause and effect.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Switched Latent Force Models for Movement Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Non-parametric estimation of integral probability metrics.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2010

The Influence of the Image Basis on Modeling and Steganalysis Performance.

[BibT_eX]

[DOI]

Valentin Schwamberger

Pham Hai Dang Le

Proceedings of the Information Hiding - 12th International Conference, 2010

Movement templates for learning of hitting and batting.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Telling cause from effect based on high-dimensional observations.

[BibT_eX]

[DOI]

Patrik O. Hoyer

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Image Processing, 2010

Efficient filter flow for space-variant multiframe blind deconvolution.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Causal Markov Condition for Submodular Information Measures.

[BibT_eX]

[DOI]

Bastian Steudel

Proceedings of the COLT 2010, 2010

2009

Prototype Classification: Insights from Machine Learning.

[BibT_eX]

[DOI]

Neural Comput., 2009

Protein functional class prediction with a combined graph.

[BibT_eX]

[DOI]

Hyunjung Shin

Expert Syst. Appl., 2009

A note on integral probability metrics and $\phi$-divergences

[BibT_eX]

[DOI]

CoRR, 2009

Identifying confounders using additive noise models.

[BibT_eX]

[DOI]

Proceedings of the UAI 2009, 2009

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Generalized Clustering via Kernel Embeddings.

[BibT_eX]

[DOI]

Stefanie Jegelka

Ulrike von Luxburg

Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

Multi-way set enumeration in real-valued tensors.

[BibT_eX]

[DOI]

Elisabeth Georgii

Proceedings of the 2nd ACM SIGKDD Workshop on Data Mining using Matrices and Tensors, 2009

Sparse online model learning for robot control with support vector regression.

[BibT_eX]

[DOI]

Duy Nguyen-Tuong

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Detecting the direction of causal time series.

[BibT_eX]

[DOI]

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Regression by dependence minimization and its application to causal inference in additive noise models.

[BibT_eX]

[DOI]

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

09401 Abstracts Collection - Machine learning approaches to statistical dependences and causality.

[BibT_eX]

[DOI]

Steffen L. Lauritzen

Proceedings of the Machine learning approaches to statistical dependences and causality, 27.09., 2009

Markerless 3D Face Tracking.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 2009

Learning similarity measure for multi-modal 3D image registration.

[BibT_eX]

[DOI]

Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008

Kernels, regularization and differential equations.

[BibT_eX]

[DOI]

Pattern Recognit., 2008

Support Vector Machines and Kernels for Computational Biology.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2008

Causal reasoning by evaluating the complexity of conditional densities with kernel methods.

[BibT_eX]

[DOI]

Xiaohai Sun

Neurocomputing, 2008

Guest Editorial.

[BibT_eX]

[DOI]

William T. Freeman

Pietro Perona

Int. J. Comput. Vis., 2008

Manifold-valued Thin-Plate Splines with Applications in Computer Graphics.

[BibT_eX]

[DOI]

Comput. Graph. Forum, 2008

Diffeomorphic Dimensionality Reduction.

[BibT_eX]

[DOI]

Gabriele Beate Schweikert

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Bayesian Experimental Design of Magnetic Resonance Imaging Sequences.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis.

[BibT_eX]

[DOI]

Christian Widmer

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Nonlinear causal discovery with additive noise models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Characteristic Kernels on Groups and Semigroups.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Sparse multiscale gaussian process regression.

[BibT_eX]

[DOI]

Kwang In Kim

Proceedings of the Machine Learning, 2008

Tailoring density estimation via reproducing kernel moment matching.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2008

Kernel Methods for Detecting the Direction of Time Series.

[BibT_eX]

[DOI]

Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008

Automatic 3D face reconstruction from single images or video.

[BibT_eX]

[DOI]

Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

Learning Inverse Dynamics: a Comparison.

[BibT_eX]

[DOI]

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

Automatic Image Colorization Via Multimodal Predictions.

[BibT_eX]

[DOI]

Guillaume Charpiat

Matthias Hofmann

Proceedings of the Computer Vision, 2008

Injective Hilbert Space Embeddings of Probability Measures.

[BibT_eX]

[DOI]

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007

Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA.

[BibT_eX]

[DOI]

IEEE Trans. Biomed. Eng., 2007

Feature Selection for Troubleshooting in Complex Assembly Lines.

[BibT_eX]

[DOI]

Tobias Pfingsten

Daniel J. L. Herrmann

Thomas Schnitzler

Andreas Feustel

IEEE Trans Autom. Sci. Eng., 2007

Improving the <i>Caenorhabditis elegans</i> Genome Annotation Using Machine Learning.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2007

Transductive Classification via Local Learning Regularization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

The Need for Open Source Software in Machine Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2007

An Analysis of Inference with the Universum.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Kernel Statistical Test of Independence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Kernel Measures of Conditional Dependence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Local learning projections.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

A kernel-based causal learning algorithm.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions.

[BibT_eX]

[DOI]

Xiaohai Sun

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 2007

Towards Machine Learning of Motor Skills.

[BibT_eX]

[DOI]

Stefan Schaal

Proceedings of the Autonome Mobile Systeme 2007, 2007

A Hilbert Space Embedding for Distributions.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

A Kernel Approach to Comparing Distributions.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

Classification of Faces in Man and Machine.

[BibT_eX]

[DOI]

Neural Comput., 2006

A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression.

[BibT_eX]

[DOI]

Neural Comput., 2006

A Direct Method for Building Sparse Kernel Learning Algorithms.

[BibT_eX]

[DOI]

Gökhan H. Bakir

J. Mach. Learn. Res., 2006

Large Scale Multiple Kernel Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2006

Implicit Surface Modelling with a Globally Regularised Basis of Compact Support.

[BibT_eX]

[DOI]

Comput. Graph. Forum, 2006

Learning with Hypergraphs: Clustering, Classification, and Embedding.

[BibT_eX]

[DOI]

Jiayuan Huang

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Local Learning Approach for Clustering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Learning Dense 3D Correspondence.

[BibT_eX]

[DOI]

Volker Blanz

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Nonparametric Approach to Bottom-Up Visual Saliency.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Correcting Sample Selection Bias by Unlabeled Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Integrating structured biological data by Kernel Maximum Mean Discrepancy.

[BibT_eX]

[DOI]

Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Causal Inference by Choosing Graphs with Most Plausible Markov Kernels.

[BibT_eX]

[DOI]

Xiaohai Sun

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals.

[BibT_eX]

[DOI]

Christian Erich Elger

Niels Birbaumer

Proceedings of the Pattern Recognition, 2006

Learning an Interest Operator from Human Eye Movements.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

Combining a Filter Method with SVMs.

[BibT_eX]

[DOI]

Thomas Navin Lal

Proceedings of the Feature Extraction - Foundations and Applications, 2006

Discrete Regularization.

[BibT_eX]

[DOI]

Proceedings of the Semi-Supervised Learning, 2006

A Discussion of Semi-Supervised Learning and Transduction.

[BibT_eX]

[DOI]

Proceedings of the Semi-Supervised Learning, 2006

Analysis of Benchmarks.

[BibT_eX]

[DOI]

Proceedings of the Semi-Supervised Learning, 2006

Introduction to Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Semi-Supervised Learning, 2006

2005

Iterative Kernel Principal Component Analysis for Image Modeling.

[BibT_eX]

[DOI]

Kwang In Kim

IEEE Trans. Pattern Anal. Mach. Intell., 2005

Experimentally optimal nu in support vector regression for different noise models and parameter settings.

[BibT_eX]

[DOI]

Athanassia Chalimourda

Neural Networks, 2005

Kernel Methods for Measuring Independence.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Maximal margin classification for metric spaces.

[BibT_eX]

[DOI]

Matthias Hein

J. Comput. Syst. Sci., 2005

Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces.

[BibT_eX]

[DOI]

EURASIP J. Adv. Signal Process., 2005

Support Vector Machines for 3D Shape Processing.

[BibT_eX]

[DOI]

Joaquin Quiñonero Candela

Volker Blanz

Comput. Graph. Forum, 2005

Evaluating Predictive Uncertainty Challenge.

[BibT_eX]

[DOI]

Fabian H. Sinz

Proceedings of the Machine Learning Challenges, 2005

Joint Kernel Maps.

[BibT_eX]

[DOI]

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach.

[BibT_eX]

[DOI]

Tobias Jung

Luis Javier Herrera

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

RASE: recognition of alternatively spliced exons in <i>C.elegans</i>.

[BibT_eX]

[DOI]

Sören Sonnenburg

Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Learning from labeled and unlabeled data on a directed graph.

[BibT_eX]

[DOI]

Jiayuan Huang

Proceedings of the Machine Learning, 2005

Building Sparse Large Margin Classifiers.

[BibT_eX]

[DOI]

Gökhan H. Bakir

Proceedings of the Machine Learning, 2005

Implicit surface modelling as an eigenvalue problem.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

Large scale genomic sequence SVM classifiers.

[BibT_eX]

[DOI]

Sören Sonnenburg

Proceedings of the Machine Learning, 2005

Object correspondence as a machine learning problem.

[BibT_eX]

[DOI]

Volker Blanz

Proceedings of the Machine Learning, 2005

A brain computer interface with online feedback based on magnetoencephalography.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

Training Support Vector Machines with Multiple Equality Constraints.

[BibT_eX]

[DOI]

Wolf Kienzle

Proceedings of the Machine Learning: ECML 2005, 2005

Fast protein classification with multiple networks.

[BibT_eX]

[DOI]

Hyunjung Shin

Proceedings of the ECCB/JBI'05 Proceedings, Fourth European Conference on Computational Biology/Sixth Meeting of the Spanish Bioinformatics Network (Jornadas de BioInformática), Palacio de Congresos, Madrid, Spain, September 28, 2005

Regularization on Discrete Spaces.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 27th DAGM Symposium, Vienna, Austria, August 31, 2005

Measuring Statistical Dependence with Hilbert-Schmidt Norms.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Kernel Constrained Covariance for Dependence Measurement.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Support vector channel selection in BCI.

[BibT_eX]

[DOI]

IEEE Trans. Biomed. Eng., 2004

A tutorial on support vector regression.

[BibT_eX]

[DOI]

Stat. Comput., 2004

Experimentally optimal v in support vector regression for different noise models and parameter settings.

[BibT_eX]

[DOI]

Athanassia Chalimourda

Neural Networks, 2004

A Compression Approach to Support Vector Model Selection.

[BibT_eX]

[DOI]

Ulrike von Luxburg

J. Mach. Learn. Res., 2004

Feature Selection for Support Vector Machines Using Genetic Algorithms.

[BibT_eX]

[DOI]

Holger Fröhlich

Int. J. Artif. Intell. Tools, 2004

Semi-supervised Learning on Directed Graphs.

[BibT_eX]

[DOI]

Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Machine Learning Applied to Perception: Decision Images for Gender Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Kernel Methods for Implicit Surface Modeling.

[BibT_eX]

[DOI]

Joachim Giesen

Simon Spalinger

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Methods Towards Invasive Human Brain Computer Interfaces.

[BibT_eX]

[DOI]

Christian Erich Elger

Niels Birbaumer

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Face Detection - Efficient and Rank Deficient.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

An Auditory Paradigm for Brain-Computer Interfaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Implicit Wiener Series for Higher-Order Image Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A kernel view of the dimensionality reduction of manifolds.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2004

Learning from Labeled and Unlabeled Data Using Random Walks.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Efficient Approximations for Support Vector Machines in Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Semi-supervised Kernel Regression Using Whitened Function Classes.

[BibT_eX]

[DOI]

Younghee Kwon

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Multivariate Regression via Stiefel Manifold Constraints.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

2003

Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2003

Use of the Zero-Norm with Linear Models and Kernel Methods.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Statistical learning theory, capacity, and complexity.

[BibT_eX]

[DOI]

Complex., 2003

Feature selection and transduction for prediction of molecular bioactivity for drug design.

[BibT_eX]

[DOI]

Bioinform., 2003

Ranking on Data Manifolds.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning with Local and Global Consistency.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Prediction on Spike Data Using Kernel Algorithms.

[BibT_eX]

[DOI]

Nikos K. Logothetis

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning to Find Pre-Images.

[BibT_eX]

[DOI]

Gökhan H. Bakir

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Feature Selection for Support Vector Machines by Means of Genetic Algorithms.

[BibT_eX]

[DOI]

Holger Fröhlich

Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2003), 2003

2002

Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2002

Training Invariant Support Vector Machines.

[BibT_eX]

[DOI]

Dennis DeCoste

Mach. Learn., 2002

Support Vector Machines and Kernel Methods: The New Generation of Learning Machines.

[BibT_eX]

[DOI]

Nello Cristianini

AI Mag., 2002

A Kernel Approach for Learning from Almost Orthogonal Patterns.

[BibT_eX]

[DOI]

William Stafford Noble

Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

Kernel Dependency Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Cluster Kernels for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Bayesian Kernel Methods.

[BibT_eX]

[DOI]

Proceedings of the Advanced Lectures on Machine Learning, 2002

A Short Introduction to Learning with Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advanced Lectures on Machine Learning, 2002

Learning with Kernels: support vector machines, regularization, optimization, and beyond.

[BibT_eX]

[DOI]

Alexander Johannes Smola

Adaptive computation and machine learning series, MIT Press, ISBN: 9780262194754, 2002

2001

An introduction to kernel-based learning algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 2001

Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators.

[BibT_eX]

[DOI]

Robert C. Williamson

IEEE Trans. Inf. Theory, 2001

Estimating the Support of a High-Dimensional Distribution.

[BibT_eX]

[DOI]

Neural Comput., 2001

Regularized Principal Manifolds.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2001

Incorporating Invariances in Non-Linear Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Sampling Techniques for Kernel Methods.

[BibT_eX]

[DOI]

Dimitris Achlioptas

Frank McSherry

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Estimating a Kernel Fisher Discriminant in the Presence of Label Noise.

[BibT_eX]

Neil D. Lawrence

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Computationally Efficient Face Detection.

[BibT_eX]

[DOI]

Proceedings of the Eighth International Conference On Computer Vision (ICCV-01), Vancouver, British Columbia, Canada, July 7-14, 2001, 2001

Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation.

[BibT_eX]

[DOI]

Proceedings of the Eighth International Conference On Computer Vision (ICCV-01), Vancouver, British Columbia, Canada, July 7-14, 2001, 2001

A Generalized Representer Theorem.

[BibT_eX]

[DOI]

Ralf Herbrich

Proceedings of the Computational Learning Theory, 2001

A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds.

[BibT_eX]

[DOI]

Michael E. Tipping

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

An improved training algorithm for kernel Fisher discriminants.

[BibT_eX]

[DOI]

Sebastian Mika

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

Statistical Learning and Kernel Methods.

[BibT_eX]

[DOI]

Proceedings of the Data Fusion and Perception, 2001

2000

New Support Vector Algorithms.

[BibT_eX]

[DOI]

Neural Comput., 2000

Engineering support vector machine kernels that recognize translation initiation sites.

[BibT_eX]

[DOI]

Bioinform., 2000

Robust Ensemble Learning for Data Mining.

[BibT_eX]

[DOI]

Proceedings of the Knowledge Discovery and Data Mining, 2000

Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

The Kernel Trick for Distances.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments.

[BibT_eX]

[DOI]

Athanassia Chalimourda

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Sparse Greedy Matrix Approximation for Machine Learning.

[BibT_eX]

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Entropy Numbers of Linear Function Classes.

[BibT_eX]

Robert C. Williamson

Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999

Input space versus feature space in kernel-based methods.

[BibT_eX]

[DOI]

Sebastian Mika

Christopher J. C. Burges

IEEE Trans. Neural Networks, 1999

Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten.

[BibT_eX]

[DOI]

Inform. Forsch. Entwickl., 1999

The Entropy Regularization Information Criterion.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Support Vector Method for Novelty Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

v-Arc: Ensemble Learning in the Presence of Outliers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Invariant Feature Extraction and Classification in Kernel Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.

[BibT_eX]

Proceedings of the German Conference on Bioinformatics, 1999

Entropy Numbers, Operators and Support Vector Kernels.

[BibT_eX]

[DOI]

Robert C. Williamson

Proceedings of the Computational Learning Theory, 4th European Conference, 1999

1998

The connection between regularization operators and support vector kernels.

[BibT_eX]

[DOI]

Neural Networks, 1998

Nonlinear Component Analysis as a Kernel Eigenvalue Problem.

[BibT_eX]

[DOI]

Neural Comput., 1998

Where did I take that snapshot? Scene-based homing by image matching.

[BibT_eX]

[DOI]

Biol. Cybern., 1998

Learning View Graphs for Robot Navigation.

[BibT_eX]

[DOI]

Auton. Robots, 1998

On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion.

[BibT_eX]

[DOI]

Algorithmica, 1998

Semiparametric Support Vector and Linear Programming Machines.

[BibT_eX]

[DOI]

Thilo-Thomas Frieß

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Shrinking the Tube: A New Support Vector Regression Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Kernel PCA and De-Noising in Feature Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces.

[BibT_eX]

[DOI]

Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

Navigation mit Schnappschüssen.

[BibT_eX]

[DOI]

Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

1997

Support vector learning.

[BibT_eX]

[DOI]

PhD thesis, 1997

Comparing support vector machines with Gaussian kernels to radial basis function classifiers.

[BibT_eX]

[DOI]

Kah Kay Sung

Christopher J. C. Burges

IEEE Trans. Signal Process., 1997

From Regularization Operators to Support Vector Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Prior Knowledge in Support Vector Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Kernel Principal Component Analysis.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 1997

Predicting Time Series with Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 1997

The View-Graph Approach to Visual Navigation and Spatial Memory.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 1997

Learning View Graphs for Robot Navigation.

[BibT_eX]

[DOI]

Proceedings of the First International Conference on Autonomous Agents, 1997

1996

Improving the Accuracy and Speed of Support Vector Machines.

[BibT_eX]

[DOI]

Christopher J. C. Burges

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Incorporating Invariances in Support Vector Learning Machines.

[BibT_eX]

[DOI]

Chris Burges

Vladimir Vapnik

Proceedings of the Artificial Neural Networks, 1996

Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 1996

1995

View-Based Cognitive Mapping and Path Planning.

[BibT_eX]

[DOI]

Hanspeter A. Mallot

Adapt. Behav., 1995

Extracting Support Data for a Given Task.

[BibT_eX]

[DOI]