Arno Solin

Theodoros Damoulas

CoRR, 2024

Sources of Uncertainty in 3D Scene Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2024

iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Improving Discrete Diffusion Models via Structured Preferential Generation.

[BibT_eX]

[DOI]

Severi Rissanen

Markus Heinonen

CoRR, 2024

Alignment is Key for Applying Diffusion Models to Retrosynthesis.

[BibT_eX]

[DOI]

CoRR, 2024

Flatness Improves Backbone Generalisation in Few-shot Classification.

[BibT_eX]

[DOI]

CoRR, 2024

Fixing Overconfidence in Dynamic Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Online One-Dimensional Magnetic Field SLAM with Loop-Closure Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2024

Function-space Parameterization of Neural Networks for Sequential Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Subtractive Mixture Models via Squaring: Representation and Learning.

[BibT_eX]

[DOI]

Lorenzo Loconte

Aleksanteri M. Sladek

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning to Approximate Particle Smoothing Trajectories via Diffusion Generative Models.

[BibT_eX]

[DOI]

Ella Tamir

Proceedings of the 27th International Conference on Information Fusion, 2024

Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Variational Gaussian Process Diffusion Processes.

[BibT_eX]

[DOI]

Prakhar Verma

Vincent Adam

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

2023

Transport with Support: Data-Conditional Diffusion Bridges.

[BibT_eX]

[DOI]

Ella Tamir

Martin Trapp

Trans. Mach. Learn. Res., 2023

Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming.

[BibT_eX]

[DOI]

Gabriel Riutort-Mayol

Paul-Christian Bürkner

Aki Vehtari

Stat. Comput., 2023

Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Sparse Function-space Representation of Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Rao-Blackwellized Particle Smoothing for Simultaneous Localization and Mapping.

[BibT_eX]

[DOI]

Thomas B. Schön

CoRR, 2023

Expansion of Visual Hints for Improved Generalization in Stereo Matching.

[BibT_eX]

[DOI]

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

MixupE: Understanding and improving Mixup from directional derivative perspective.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models.

[BibT_eX]

[DOI]

Rui Li

S. T. John

Proceedings of the International Conference on Machine Learning, 2023

Memory-Based Dual Gaussian Processes for Sequential Learning.

[BibT_eX]

[DOI]

Mohammad Emtiyaz Khan

Proceedings of the International Conference on Machine Learning, 2023

Generative Modelling with Inverse Heat Dissipation.

[BibT_eX]

[DOI]

Severi Rissanen

Markus Heinonen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Robust Semantic Segmentation UNCV2023 Challenge Results.

[BibT_eX]

[DOI]

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

2022

Interpolation consistency training for semi-supervised learning.

[BibT_eX]

[DOI]

Neural Networks, 2022

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective.

[BibT_eX]

[DOI]

CoRR, 2022

Towards Improved Learning in Gaussian Processes: The Best of Two Worlds.

[BibT_eX]

[DOI]

Rui Li

S. T. John

CoRR, 2022

Fantasizing with Dual GPs in Bayesian Optimization and Active Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Representational Multiplicity Should Be Exposed, Not Eliminated.

[BibT_eX]

[DOI]

CoRR, 2022

HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

A Look at Improving Robustness in Visual- inertial SLAM by Moment Matching.

[BibT_eX]

[DOI]

Rui Li

Andrea Pilzer

Proceedings of the 25th International Conference on Information Fusion, 2022

Uncertainty-Guided Source-Free Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Non-separable Spatio-temporal Graph Kernels via SPDEs.

[BibT_eX]

[DOI]

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

2021

Novel View Synthesis via Depth-guided Skip Connections.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Combining pseudo-point and state space approximations for sum-separable Gaussian Processes.

[BibT_eX]

[DOI]

Will Tebbutt

Richard E. Turner

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov Equation.

[BibT_eX]

[DOI]

Ella Tamir

Prakhar Verma

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

Periodic Activation Functions Induce Stationarity.

[BibT_eX]

[DOI]

Lassi Meronen

Martin Trapp

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

Spatio-Temporal Variational Gaussian Processes.

[BibT_eX]

[DOI]

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

Dual Parameterization of Sparse Variational Gaussian Processes.

[BibT_eX]

[DOI]

Vincent Adam

Paul E. Chang

Mohammad Emtiyaz Khan

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

Sparse Algorithms for Markovian Gaussian Processes.

[BibT_eX]

[DOI]

Vincent Adam

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

Gaussian Process Priors for View-Aware Inference.

[BibT_eX]

[DOI]

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

2020

Hilbert space methods for reduced-rank Gaussian process regression.

[BibT_eX]

[DOI]

Stat. Comput., 2020

RealAnt: An Open-Source Low-Cost Quadruped for Research in Real-World Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Residual Mixture Models.

[BibT_eX]

[DOI]

Perttu Hämäläinen

CoRR, 2020

Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Stationary Activations for Uncertainty Calibration in Deep Learning.

[BibT_eX]

[DOI]

Lassi Meronen

Christabella Irwanto

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

Deep Automodulators.

[BibT_eX]

[DOI]

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

Fast Variational Learning in State-Space Gaussian Process Models.

[BibT_eX]

[DOI]

Paul E. Chang

Mohammad Emtiyaz Khan

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Movement-induced Priors for Deep Stereo.

[BibT_eX]

[DOI]

Muhammad Kamran Janjua

Proceedings of the 25th International Conference on Pattern Recognition, 2020

State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes.

[BibT_eX]

[DOI]

Paul E. Chang

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

Scalable Exact Inference in Multi-Output Gaussian Processes.

[BibT_eX]

[DOI]

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

Movement Tracking by Optical Flow Assisted Inertial Navigation.

[BibT_eX]

[DOI]

Lassi Meronen

Proceedings of the IEEE 23rd International Conference on Information Fusion, 2020

2019

Unstructured Multi-view Depth Estimation Using Mask-Based Multiplane Representation.

[BibT_eX]

[DOI]

Proceedings of the Image Analysis - 21st Scandinavian Conference, 2019

End-to-End Probabilistic Inference for Nonstationary Audio Analysis.

[BibT_eX]

[DOI]

Joshua D. Reiss

Dan Stowell

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

Multi-View Stereo by Temporal Nonparametric Fusion.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Unifying Probabilistic Models for Time-frequency Analysis.

[BibT_eX]

[DOI]

Joshua D. Reiss

Dan Stowell

Proceedings of the IEEE International Conference on Acoustics, 2019

Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones.

[BibT_eX]

[DOI]

Proceedings of the 22th International Conference on Information Fusion, 2019

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

ADVIO: An Authentic Dataset for Visual-Inertial Odometry.

[BibT_eX]

[DOI]

Dataset, July, 2018

ADVIO: An Authentic Dataset for Visual-Inertial Odometry.

[BibT_eX]

[DOI]

Dataset, July, 2018

ADVIO: An Authentic Dataset for Visual-Inertial Odometry.

[BibT_eX]

[DOI]

Dataset, July, 2018

Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes.

[BibT_eX]

[DOI]

IEEE Trans. Robotics, 2018

Computationally Inferred Genealogical Networks Uncover Long-Term Trends in Assortative Mating.

[BibT_eX]

[DOI]

Eric Malmi

Aristides Gionis

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

PIVO: Probabilistic Inertial-Visual Odometry for Occlusion-Robust Navigation.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Infinite-Horizon Gaussian Processes.

[BibT_eX]

[DOI]

James Hensman

Richard E. Turner

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

Deep Learning based Speed estimation for Constraining Strapdown inertial Navigation on Smartphones.

[BibT_eX]

[DOI]

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

State Space Gaussian Processes with Non-Gaussian Likelihood.

[BibT_eX]

[DOI]

Hannes Nickisch

Alexander Grigorevskiy

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

Inertial Odometry on Handheld Smartphones.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Information Fusion, 2018

Robust Gyroscope-Aided Camera Self-Calibration.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Information Fusion, 2018

Scalable Magnetic Field SLAM in 3D Using Gaussian Process Maps.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Information Fusion, 2018

ADVIO: An Authentic Dataset for Visual-Inertial Odometry.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Recursive Chaining of Reversible Image-to-Image Translators for Face Aging.

[BibT_eX]

[DOI]

Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2018

Pioneer Networks: Progressively Growing Generative Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

Variational Fourier Features for Gaussian Processes.

[BibT_eX]

[DOI]

James Hensman

Nicolas Durrande

J. Mach. Learn. Res., 2017

2016

Computationally Efficient Bayesian Learning of Gaussian Process State Space Models.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

The Blind Leading the Blind: Network-Based Location Estimation Under Uncertainty.

[BibT_eX]

[DOI]

Eric Malmi

Aristides Gionis

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Nonlinear state space model identification using a regularized basis function expansion.

[BibT_eX]

[DOI]

Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

State Space Methods for Efficient Inference in Student-t Process Regression.

[BibT_eX]

[DOI]

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

2014

The 10th annual MLSP competition: First place.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Gaussian quadratures for state space approximation of scale mixtures of squared exponential covariance functions.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Expectation maximization based parameter estimation by sigma-point and particle smoothing.

[BibT_eX]

[DOI]

Juho Kokkala

Proceedings of the 17th International Conference on Information Fusion, 2014

Explicit Link Between Periodic Covariance Functions and State Space Models.

[BibT_eX]

[DOI]

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

2013

Spatiotemporal Learning via Infinite-Dimensional Bayesian Filtering and Smoothing: A Look at Gaussian Process Regression Through Kalman Filtering.

[BibT_eX]

[DOI]

Jouni Hartikainen

IEEE Signal Process. Mag., 2013

Continuous-Space Gaussian Process Regression and Generalized Wiener Filtering with Application to Learning Curves.

[BibT_eX]

[DOI]