Stefano Ermon

Orcid: 0000-0003-0039-2887

Affiliations:
  • Stanford University


According to our database1, Stefano Ermon authored at least 353 papers between 2009 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives.
Mach. Learn. Sci. Technol., March, 2024

TrAct: Making First-layer Pre-Activations Trainable.
CoRR, 2024

<i>f</i>-PO: Generalizing Preference Optimization with <i>f</i>-divergence Minimization.
CoRR, 2024

Energy-Based Diffusion Language Models for Text Generation.
CoRR, 2024

TabDiff: a Multi-Modal Diffusion Model for Tabular Data Generation.
CoRR, 2024

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms.
CoRR, 2024

Mitigating Embedding Collapse in Diffusion Models for Categorical Data.
CoRR, 2024

G2D2: Gradient-guided Discrete Diffusion for image inverse problem solving.
CoRR, 2024

Geometric Trajectory Diffusion Models.
CoRR, 2024

Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation.
CoRR, 2024

Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis.
CoRR, 2024

TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data.
CoRR, 2024

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation.
CoRR, 2024

Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space.
CoRR, 2024

Calibrated Probabilistic Forecasts for Arbitrary Sequences.
CoRR, 2024

TFG: Unified Training-Free Guidance for Diffusion Models.
CoRR, 2024

CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion.
CoRR, 2024

Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes.
CoRR, 2024

Unsupervised Anomaly Detection Using Diffusion Trend Analysis.
CoRR, 2024

Consistency Flow Matching: Defining Straight Flows with Velocity Consistency.
CoRR, 2024

Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization.
CoRR, 2024

Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model.
CoRR, 2024

TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning.
CoRR, 2024

ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts.
CoRR, 2024

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher.
CoRR, 2024

Segment Any Change.
CoRR, 2024

Equivariant Graph Neural Operator for Modeling 3D Dynamics.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mechanistic Design and Scaling of Hybrid Architectures.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

State-Free Inference of State-Space Models: The *Transfer Function* Approach.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Large Language Models are Geographically Biased.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Denoising Diffusion Bridge Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language Model Detectors Are Easily Optimized Against.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

GeoLLM: Extracting Geospatial Knowledge from Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DiffusionSat: A Generative Foundation Model for Satellite Imagery.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Manifold Preserving Guided Diffusion.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TorchSpatial: A Python Package for Spatial Representation Learning and Geo-Aware Model Development.
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications, 2024

DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Diffusion Model Alignment Using Direct Preference Optimization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

On the Scalability of Diffusion-based Text-to-Image Generation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

HIVE: Harnessing Human Feedback for Instructional Visual Editing.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Disentangling Length from Quality in Direct Preference Optimization.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

HarvestNet: A Dataset for Detecting Smallholder Farming Activity Using Harvest Piles and Remote Sensing.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Towards general-purpose representation learning of polygonal geometries.
GeoInformatica, April, 2023

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Trans. Mach. Learn. Res., 2023

MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning.
Trans. Mach. Learn. Res., 2023

Neural Network Compression for Noisy Storage Devices.
ACM Trans. Embed. Comput. Syst., 2023

Equivariant Flow Matching with Hybrid Probability Transport.
CoRR, 2023

Calibration by Distribution Matching: Trainable Kernel Calibration Metrics.
CoRR, 2023

Scaling Riemannian Diffusion Models.
CoRR, 2023

Generative Fractional Diffusion Models.
CoRR, 2023

Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution.
CoRR, 2023

SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution.
CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR, 2023

Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions.
CoRR, 2023

On the Equivalence of Consistency-Type Models: Consistency Models, Consistent Diffusion Models, and Fokker-Planck Regularization.
CoRR, 2023

MADiff: Offline Multi-agent Learning with Diffusion Models.
CoRR, 2023

Building Coverage Estimation with Low-resolution Remote Sensing Imagery.
CoRR, 2023

SIGGRAPH 2023 Course on Diffusion Models.
Proceedings of the ACM SIGGRAPH 2023 Courses, 2023

Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Parallel Sampling of Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Direct Preference Optimization: Your Language Model is Secretly a Reward Model.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Calibration by Distribution Matching: Trainable Kernel Calibration Metrics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Riemannian Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Holistic Evaluation of Text-to-Image Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MUDiff: Unified Diffusion for Complete Molecule Generation.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Graph and Geometry Generative Modeling for Drug Discovery.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Deep Latent State Space Models for Time-Series Generation.
Proceedings of the International Conference on Machine Learning, 2023

Geometric Latent Diffusion Models for 3D Molecule Generation.
Proceedings of the International Conference on Machine Learning, 2023

Long Horizon Temperature Scaling.
Proceedings of the International Conference on Machine Learning, 2023

Hyena Hierarchy: Towards Larger Convolutional Language Models.
Proceedings of the International Conference on Machine Learning, 2023

GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration.
Proceedings of the International Conference on Machine Learning, 2023

CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations.
Proceedings of the International Conference on Machine Learning, 2023

Reflected Diffusion Models.
Proceedings of the International Conference on Machine Learning, 2023

FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation.
Proceedings of the International Conference on Machine Learning, 2023

Dual Diffusion Implicit Bridges for Image-to-Image Translation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Understanding and Adopting Rational Behavior by Bellman Score Estimation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Extreme Q-Learning: MaxEnt RL without Entropy.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generative Modeling Helps Weak Supervision (and Vice Versa).
Proceedings of the Eleventh International Conference on Learning Representations, 2023

End-to-End Diffusion Latent Optimization Improves Classifier Guidance.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models.
Proceedings of the Proceedings on "I Can't Believe It's Not Better: Failure Modes in the Age of Foundation Models" at NeurIPS 2023 Workshops, 2023

On Distillation of Guided Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Ideal Abstractions for Decision-Focused Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
LMPriors: Pre-Trained Language Models as Task-Specific Priors.
CoRR, 2022

Regularizing Score-based Models with Score Fokker-Planck Equations.
CoRR, 2022

On Distillation of Guided Diffusion Models.
CoRR, 2022

JPEG Artifact Correction using Denoising Diffusion Restoration Models.
CoRR, 2022

Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements.
CoRR, 2022

Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution.
CoRR, 2022

Local calibration: metrics and recalibration.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Training and Inference on Any-Order Autoregressive Models the Right Way.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transform Once: Efficient Operator Learning in Frequency Domain.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalizing Bayesian Optimization with Decision-theoretic Entropies.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Concrete Score Matching: Generalized Score Matching for Discrete Data.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploration via Planning for Information about the Optimal Trajectory.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Denoising Diffusion Restoration Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LISA: Learning Interpretable Skill Abstractions from Language.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Self-Supervised Learning by Characterizing Idealized Representations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Experience Replay with Likelihood-free Importance Weights.
Proceedings of the Learning for Dynamics and Control Conference, 2022

A General Recipe for Likelihood-free Bayesian Optimization.
Proceedings of the International Conference on Machine Learning, 2022

Bit Prioritization in Variational Autoencoders via Progressive Coding.
Proceedings of the International Conference on Machine Learning, 2022

ButterflyFlow: Building Invertible Layers with Butterfly Matrices.
Proceedings of the International Conference on Machine Learning, 2022

Modular Conformal Calibration.
Proceedings of the International Conference on Machine Learning, 2022

Imitation Learning by Estimating Expertise of Demonstrators.
Proceedings of the International Conference on Machine Learning, 2022

Comparing Distributions by Measuring Differences that Affect Decision Making.
Proceedings of the Tenth International Conference on Learning Representations, 2022

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

An Experimental Design Perspective on Model-Based Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Conditional Imitation Learning for Multi-Agent Games.
Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 2022

Towards a foundation model for geospatial artificial intelligence (vision paper).
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Understanding economic development in rural Africa using satellite imagery, building footprints and deep models.
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Efficient Conditional Pre-training for Transfer Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Density Ratio Estimation via Infinitesimal Classification.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Scalable deep learning to identify brick kilns and aid regulatory capacity.
Proc. Natl. Acad. Sci. USA, 2021

Quantifying and Understanding Adversarial Examples in Discrete Input Spaces.
CoRR, 2021

A Unified Framework for Multi-distribution Density Ratio Estimation.
CoRR, 2021

Equivariant Neural Network for Factor Graphs.
CoRR, 2021

On the Opportunities and Risks of Foundation Models.
CoRR, 2021

SDEdit: Image Synthesis and Editing with Stochastic Differential Equations.
CoRR, 2021

D2C: Diffusion-Denoising Models for Few-shot Conditional Generation.
CoRR, 2021

Localized Calibration: Metrics and Recalibration.
CoRR, 2021

Featurized density ratio estimation.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Multi-agent Imitation Learning with Copulas.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Pseudo-Spherical Contrastive Divergence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Improving Compositionality of Neural Networks by Decoding Representations to Inputs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PiRank: Scalable Learning To Rank via Differentiable Sorting.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Maximum Likelihood Training of Score-Based Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

HyperSPNs: Compact and Expressive Probabilistic Circuits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reliable Decisions with Threshold Calibration.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Estimating High Order Gradients of the Data Distribution by Denoising.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Imitation with Neural Density Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

IQ-Learn: Inverse soft-Q Learning for Imitation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Challenges in KDD and ML for Sustainable Development.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving.
Proceedings of the 38th International Conference on Machine Learning, 2021

Temporal Predictive Coding For Model-Based Planning In Latent Space.
Proceedings of the 38th International Conference on Machine Learning, 2021

Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information.
Proceedings of the 38th International Conference on Machine Learning, 2021

Reward Identification in Inverse Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.
Proceedings of the 9th International Conference on Learning Representations, 2021

Anytime Sampling for Autoregressive Models via Ordered Autoencoding.
Proceedings of the 9th International Conference on Learning Representations, 2021

Denoising Diffusion Implicit Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Negative Data Augmentation.
Proceedings of the 9th International Conference on Learning Representations, 2021

On the Critical Role of Conventions in Adaptive Human-AI Collaboration.
Proceedings of the 9th International Conference on Learning Representations, 2021

Improved Autoregressive Modeling with Distribution Smoothing.
Proceedings of the 9th International Conference on Learning Representations, 2021

Score-Based Generative Modeling through Stochastic Differential Equations.
Proceedings of the 9th International Conference on Learning Representations, 2021

Geography-Aware Self-Supervised Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Efficient Poverty Mapping from High Resolution Remote Sensing Images.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Domain Adaptation for Human Fall Detection Using WiFi Channel State Information.
Proceedings of the Precision Health and Medicine - A Digital Revolution in Healthcare, 2020

Closed-loop optimization of fast-charging protocols for batteries with machine learning.
Nat., 2020

Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients.
CoRR, 2020

PiRank: Learning To Rank via Differentiable Sorting.
CoRR, 2020

Using satellite imagery to understand and promote sustainable development.
CoRR, 2020

Understanding Classifier Mistakes with Generative Models.
CoRR, 2020

Privacy Preserving Recalibration under Domain Shift.
CoRR, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
CoRR, 2020

Unsupervised Calibration under Covariate Shift.
CoRR, 2020

Predicting Livelihood Indicators from Crowdsourced Street Level Images.
CoRR, 2020

Efficient Poverty Mapping using Deep Reinforcement Learning.
CoRR, 2020

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.
CoRR, 2020

Farmland Parcel Delineation Using Spatio-temporal Convolutional Networks.
CoRR, 2020

Output Diversified Initialization for Adversarial Attacks.
CoRR, 2020

Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation.
CoRR, 2020

Efficient Object Detection in Large Images Using Deep Reinforcement Learning.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Flexible Approximate Inference via Stratified Normalizing Flows.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

MOPO: Model-based Offline Policy Optimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Diversity can be Transferred: Output Diversification for White- and Black-box Attacks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multi-label Contrastive Predictive Coding.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Probabilistic Circuits for Variational Inference in Discrete Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

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

HiPPO: Recurrent Memory with Optimal Polynomial Projections.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improved Techniques for Training Score-Based Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generating Interpretable Poverty Maps using Object Detection in Satellite Images.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Individual Calibration with Randomized Forecasting.
Proceedings of the 37th International Conference on Machine Learning, 2020

Training Deep Energy-Based Models with f-Divergence Minimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Bridging the Gap Between f-GANs and Wasserstein GANs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Predictive Coding for Locally-Linear Control.
Proceedings of the 37th International Conference on Machine Learning, 2020

Domain Adaptive Imitation Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Fair Generative Modeling via Weak Supervision.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Theory of Usable Information under Computational Constraints.
Proceedings of the 8th International Conference on Learning Representations, 2020

Understanding the Limitations of Variational Mutual Information Estimators.
Proceedings of the 8th International Conference on Learning Representations, 2020

Weakly Supervised Disentanglement with Guarantees.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning When and Where to Zoom With Deep Reinforcement Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Farm Parcel Delineation Using Spatio-temporal Convolutional Networks.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

A Framework for Sample Efficient Interval Estimation with Control Variates.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Permutation Invariant Graph Generation via Score-Based Generative Modeling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

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

Meta-Amortized Variational Inference and Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Approximating Human Judgment of Generated Image Quality.
CoRR, 2019

Fair Generative Modeling via Weak Supervision.
CoRR, 2019

Unsupervised Out-of-Distribution Detection with Batch Normalization.
CoRR, 2019

Cross Domain Imitation Learning.
CoRR, 2019

Learning to Interpret Satellite Images in Global Scale Using Wikipedia.
CoRR, 2019

Distributed generation of privacy preserving data with user customization.
CoRR, 2019

Semi-Supervised Multitask Learning on Multispectral Satellite Images Using Wasserstein Generative Adversarial Networks (GANs) for Predicting Poverty.
CoRR, 2019

Differentiable Subset Sampling.
CoRR, 2019

Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning.
CoRR, 2019

Computational sustainability: computing for a better world and a sustainable future.
Commun. ACM, 2019

Sliced Score Matching: A Scalable Approach to Density and Score Estimation.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adaptive Hashing for Model Counting.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

MintNet: Building Invertible Neural Networks with Masked Convolutions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generative Modeling by Estimating Gradients of the Data Distribution.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Approximating the Permanent by Sampling from Adaptive Partitions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Predicting Economic Development using Geolocated Wikipedia Articles.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Reparameterizable Subset Sampling via Continuous Relaxations.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning to Interpret Satellite Images using Wikipedia.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Multi-Agent Adversarial Inverse Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Adaptive Antithetic Sampling for Variance Reduction.
Proceedings of the 36th International Conference on Machine Learning, 2019

Calibrated Model-Based Deep Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Graphite: Iterative Generative Modeling of Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Neural Joint Source-Channel Coding.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Neural PDE Solvers with Convergence Guarantees.
Proceedings of the 7th International Conference on Learning Representations, 2019

Stochastic Optimization of Sorting Networks via Continuous Relaxations.
Proceedings of the 7th International Conference on Learning Representations, 2019

Bias Correction of Learned Generative Models via Likelihood-free Importance Weighting.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

AlignFlow: Learning from multiple domains via normalizing flows.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Semantic Segmentation of Crop Type in Africa: A Novel Dataset and Analysis of Deep Learning Methods.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Learning Controllable Fair Representations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Training Variational Autoencoders with Buffered Stochastic Variational Inference.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

InfoVAE: Balancing Learning and Inference in Variational Autoencoders.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
NECST: Neural Joint Source-Channel Coding.
CoRR, 2018

Improved Training with Curriculum GANs.
CoRR, 2018

The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models.
CoRR, 2018

Generative Adversarial Examples.
CoRR, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
CoRR, 2018

Learning with Weak Supervision from Physics and Data-Driven Constraints.
AI Mag., 2018

A Lagrangian Perspective on Latent Variable Generative Models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Bayesian optimization and attribute adjustment.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Bias and Generalization in Deep Generative Models: An Empirical Study.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Constructing Unrestricted Adversarial Examples with Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-Agent Generative Adversarial Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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

Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Streamlining Variational Inference for Constraint Satisfaction Problems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Adversarial Constraint Learning for Structured Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
Proceedings of the 35th International Conference on Machine Learning, 2018

Accurate Uncertainties for Deep Learning Using Calibrated Regression.
Proceedings of the 35th International Conference on Machine Learning, 2018

Modeling Sparse Deviations for Compressed Sensing using Generative Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

A DIRT-T Approach to Unsupervised Domain Adaptation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data.
Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 2018

End-to-End Learning of Motion Representation for Video Understanding.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Best arm identification in multi-armed bandits with delayed feedback.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Variational Rejection Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Approximate Inference via Weighted Rademacher Complexity.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Boosted Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Shape optimization in laminar flow with a label-guided variational autoencoder.
CoRR, 2017

Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans.
CoRR, 2017

Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning.
CoRR, 2017

A Survey of Human Activity Recognition Using WiFi CSI.
CoRR, 2017

InfoVAE: Information Maximizing Variational Autoencoders.
CoRR, 2017

Towards Deeper Understanding of Variational Autoencoding Models.
CoRR, 2017

Learning Hierarchical Features from Generative Models.
CoRR, 2017

On the Limits of Learning Representations with Label-Based Supervision.
CoRR, 2017

Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs.
CoRR, 2017

Flow-GAN: Bridging implicit and prescribed learning in generative models.
CoRR, 2017

A Survey on Behavior Recognition Using WiFi Channel State Information.
IEEE Commun. Mag., 2017

Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Hybrid Deep Discriminative/Generative Models for Semi-Supervised Learning.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Stencil Autotuning with Ordinal Regression: Extended Abstract.
Proceedings of the 20th International Workshop on Software and Compilers for Embedded Systems, 2017

A-NICE-MC: Adversarial Training for MCMC.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Neural Variational Inference and Learning in Undirected Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Autotuning Stencil Computations with Structural Ordinal Regression Learning.
Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

Learning Hierarchical Features from Deep Generative Models.
Proceedings of the 34th International Conference on Machine Learning, 2017

Generative Adversarial Learning of Markov Chains.
Proceedings of the 5th International Conference on Learning Representations, 2017

Audio Super-Resolution using Neural Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep Feature Learning.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Label-Free Supervision of Neural Networks with Physics and Domain Knowledge.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Estimating Uncertainty Online Against an Adversary.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Reliable Confidence Estimation via Online Learning.
CoRR, 2016

Sparse Gaussian Processes for Bayesian Optimization.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Adaptive Concentration Inequalities for Sequential Decision Problems.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Solving Marginal MAP Problems with NP Oracles and Parity Constraints.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Generative Adversarial Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variational Bayes on Monte Carlo Steroids.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variable Elimination in the Fourier Domain.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning and Inference via Maximum Inner Product Search.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Model-Free Imitation Learning with Policy Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Tight Variational Bounds via Random Projections and I-Projections.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Closing the Gap Between Short and Long XORs for Model Counting.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Exact Sampling with Integer Linear Programs and Random Perturbations.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Decision Making And Inference Under Limited Information And High Dimensionality.
PhD thesis, 2015

Importance Sampling over Sets: A New Probabilistic Inference Scheme.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem: Application to Materials Discovery.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A Hybrid Approach for Probabilistic Inference using Random Projections.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem.
Proceedings of the Computational Sustainability, 2015

Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Low-density Parity Constraints for Hashing-Based Discrete Integration.
Proceedings of the 31th International Conference on Machine Learning, 2014

Uncovering Hidden Structure through Parallel Problem Decomposition.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Designing Fast Absorbing Markov Chains.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Learning policies for battery usage optimization in electric vehicles.
Mach. Learn., 2013

Optimization With Parity Constraints: From Binary Codes to Discrete Integration.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Embed and Project: Discrete Sampling with Universal Hashing.
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

Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Uniform Solution Sampling Using a Constraint Solver As an Oracle.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

SMT-Aided Combinatorial Materials Discovery.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2012, 2012

Feature-Enhanced Probabilistic Models for Diffusion Network Inference.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Density Propagation and Improved Bounds on the Partition Function.
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

Probabilistic planning with non-linear utility functions and worst-case guarantees.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
Accelerated Adaptive Markov Chain for Partition Function Computation.
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

A Flat Histogram Method for Computing the Density of States of Combinatorial Problems.
Proceedings of the IJCAI 2011, 2011

Risk-Sensitive Policies for Sustainable Renewable Resource Allocation.
Proceedings of the IJCAI 2011, 2011

A message passing approach to multiagent gaussian inference for dynamic processes.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

2010
Playing games against nature: optimal policies for renewable resource allocation.
Proceedings of the UAI 2010, 2010

Computing the Density of States of Boolean Formulas.
Proceedings of the Principles and Practice of Constraint Programming - CP 2010, 2010

Collaborative multiagent Gaussian inference in a dynamic environment using belief propagation.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

2009
Trust Estimation in autonomic networks: a statistical mechanics approach.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009


  Loading...