Bernhard Schölkopf

Affiliations:
  • Max Planck Institute for Intelligent Systems, Tübingen, Germany


According to our database1, Bernhard Schölkopf authored at least 698 papers between 1995 and 2024.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2017, "For contributions to the theory and practice of machine learning".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals.
CoRR, 2024

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models.
CoRR, 2024

The Essential Role of Causality in Foundation World Models for Embodied AI.
CoRR, 2024

Limits of Transformer Language Models on Learning Algorithmic Compositions.
CoRR, 2024

Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light.
CoRR, 2024

A Probabilistic Model to explain Self-Supervised Representation Learning.
CoRR, 2024

Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?
CoRR, 2024

Identifying Policy Gradient Subspaces.
CoRR, 2024

RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks.
CoRR, 2024

2023
Kernel-Based Independence Tests for Causal Structure Learning on Functional Data.
Entropy, December, 2023

Reinforcement learning with model-based feedforward inputs for robotic table tennis.
Auton. Robots, December, 2023

normflows: A PyTorch Package for Normalizing Flows.
J. Open Source Softw., July, 2023

normflows: A PyTorch Package for Normalizing Flows.
Dataset, July, 2023

Evaluating vaccine allocation strategies using simulation-assisted causal modeling.
Patterns, June, 2023

normflows: A PyTorch Package for Normalizing Flows.
Dataset, June, 2023

normflows: A PyTorch Package for Normalizing Flows.
Dataset, June, 2023


Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases.
PLoS Comput. Biol., January, 2023

Jacobian-based Causal Discovery with Nonlinear ICA.
Trans. Mach. Learn. Res., 2023

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning.
PLoS Comput. Biol., 2023

Metrizing Weak Convergence with Maximum Mean Discrepancies.
J. Mach. Learn. Res., 2023

A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations.
ACM Comput. Surv., 2023

Independent Mechanism Analysis and the Manifold Hypothesis.
CoRR, 2023

Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling.
CoRR, 2023

GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs.
CoRR, 2023

Targeted Reduction of Causal Models.
CoRR, 2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations.
CoRR, 2023

Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures.
CoRR, 2023

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.
CoRR, 2023

CausalCite: A Causal Formulation of Paper Citations.
CoRR, 2023

Causal Modeling with Stationary Diffusions.
CoRR, 2023

Ghost on the Shell: An Expressive Representation of General 3D Shapes.
CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
CoRR, 2023

Deep Backtracking Counterfactuals for Causally Compliant Explanations.
CoRR, 2023

Borges and AI.
CoRR, 2023

Investigating the Impact of Action Representations in Policy Gradient Algorithms.
CoRR, 2023

Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks.
CoRR, 2023

A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions.
CoRR, 2023

The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks.
CoRR, 2023

Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80.
CoRR, 2023

Can Large Language Models Infer Causation from Correlation?
CoRR, 2023

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding.
CoRR, 2023

Voices of Her: Analyzing Gender Differences in the AI Publication World.
CoRR, 2023

All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations.
CoRR, 2023

Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good.
CoRR, 2023

Psychologically-Inspired Causal Prompts.
CoRR, 2023

Out-of-Variable Generalization.
CoRR, 2023

Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning.
CoRR, 2023

Posterior Annealing: Fast Calibrated Uncertainty for Regression.
CoRR, 2023

The passive symmetries of machine learning.
CoRR, 2023

Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion.
CoRR, 2023

Causal effect estimation from observational and interventional data through matrix weighted linear estimators.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Hindsight States: Blending Sim & Real Task Elements for Efficient Reinforcement Learning.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Flow Matching for Scalable Simulation-Based Inference.
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.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Component Analysis.
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.
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.
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.
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.
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.
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.
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.
Proceedings of the Learning for Dynamics and Control Conference, 2023

Data-Efficient Online Learning of Ball Placement in Robot Table Tennis.
IROS, 2023

AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Discrete Key-Value Bottleneck.
Proceedings of the International Conference on Machine Learning, 2023

The Hessian perspective into the Nature of Convolutional Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Diffusion Based Representation Learning.
Proceedings of the International Conference on Machine Learning, 2023

Estimation Beyond Data Reweighting: Kernel Method of Moments.
Proceedings of the International Conference on Machine Learning, 2023

Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions.
Proceedings of the International Conference on Machine Learning, 2023

On the Relationship Between Explanation and Prediction: A Causal View.
Proceedings of the International Conference on Machine Learning, 2023

On the Identifiability and Estimation of Causal Location-Scale Noise Models.
Proceedings of the International Conference on Machine Learning, 2023

Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels.
Proceedings of the International Conference on Machine Learning, 2023

On Data Manifolds Entailed by Structural Causal Models.
Proceedings of the International Conference on Machine Learning, 2023

Provably Learning Object-Centric Representations.
Proceedings of the International Conference on Machine Learning, 2023

Bridging the Gap to Real-World Object-Centric Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Flow Annealed Importance Sampling Bootstrap.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Structure by Architecture: Structured Representations without Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Benchmarking Offline Reinforcement Learning on Real-Robot Hardware.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Pairwise Similarity Learning is SimPLE.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Glare Removal for Astronomical Images with High Local Dynamic Range.
Proceedings of the IEEE International Conference on Computational Photography, 2023

Robustness Implies Fairness in Causal Algorithmic Recourse.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

On the Interventional Kullback-Leibler Divergence.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

Unsupervised Object Learning via Common Fate.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

Dataflow graphs as complete causal graphs.
Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

Iterative Teaching by Data Hallucination.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

BaCaDI: Bayesian Causal Discovery with Unknown Interventions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models.
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.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022


Age-stratified Covid-19 case fatality rates (CFRs): different countries and longitudinal.
Dataset, May, 2022

Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots.
ACM Trans. Spatial Algorithms Syst., 2022

Learning to Play Table Tennis From Scratch Using Muscular Robots.
IEEE Trans. Robotics, 2022

Causal Feature Selection via Orthogonal Search.
Trans. Mach. Learn. Res., 2022

Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images.
IEEE Trans. Geosci. Remote. Sens., 2022

Understanding Stereotypes in Language Models: Towards Robust Measurement and Zero-Shot Debiasing.
CoRR, 2022

Evaluating vaccine allocation strategies using simulation-assisted causal modelling.
CoRR, 2022

Adapting to noise distribution shifts in flow-based gravitational-wave inference.
CoRR, 2022

FED-CD: Federated Causal Discovery from Interventional and Observational Data.
CoRR, 2022

A General Purpose Neural Architecture for Geospatial Systems.
CoRR, 2022

Spectral Representation Learning for Conditional Moment Models.
CoRR, 2022

AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation.
CoRR, 2022

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference.
CoRR, 2022

When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment.
CoRR, 2022

Probing the Robustness of Independent Mechanism Analysis for Representation Learning.
CoRR, 2022

Variational Causal Dynamics: Discovering Modular World Models from Interventions.
CoRR, 2022

Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework.
CoRR, 2022

From Statistical to Causal Learning.
CoRR, 2022

On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective".
CoRR, 2022

Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.
CoRR, 2022

Physical Derivatives: Computing policy gradients by physical forward-propagation.
CoRR, 2022

Learning soft interventions in complex equilibrium systems.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles.
Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Assaying Out-Of-Distribution Generalization in Transfer Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

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

AutoML Two-Sample Test.
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.
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.
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.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions.
Proceedings of the International Conference on Machine Learning, 2022

Action-Sufficient State Representation Learning for Control with Structural Constraints.
Proceedings of the International Conference on Machine Learning, 2022

Causal Inference Through the Structural Causal Marginal Problem.
Proceedings of the International Conference on Machine Learning, 2022

On the Adversarial Robustness of Causal Algorithmic Recourse.
Proceedings of the International Conference on Machine Learning, 2022

Generalization and Robustness Implications in Object-Centric Learning.
Proceedings of the International Conference on Machine Learning, 2022

Adversarial Robustness Through the Lens of Causality.
Proceedings of the Tenth International Conference on Learning Representations, 2022

The Role of Pretrained Representations for the OOD Generalization of RL Agents.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Phenomenology of Double Descent in Finite-Width Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain.
Proceedings of the Tenth International Conference on Learning Representations, 2022

You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Invariant Causal Representation Learning for Out-of-Distribution Generalization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Group equivariant neural posterior estimation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Differentially Private Language Models for Secure Data Sharing.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Logical Fallacy Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Structural Causal 3D Reconstruction.
Proceedings of the Computer Vision - ECCV 2022, 2022

Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Principled Disentanglement for Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Total Recall in Industrial Anomaly Detection.
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.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Learning Random Feature Dynamics for Uncertainty Quantification.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Adversarially Robust Kernel Smoothing.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Resampling Base Distributions of Normalizing Flows.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

A Witness Two-Sample Test.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

A prior-based approximate latent Riemannian metric.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On the Fairness of Causal Algorithmic Recourse.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Causality for Machine Learning.
Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021
ArmSym: A Virtual Human-Robot Interaction Laboratory for Assistive Robotics.
IEEE Trans. Hum. Mach. Syst., 2021

Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects.
IEEE Trans. Artif. Intell., 2021

Toward Causal Representation Learning.
Proc. IEEE, 2021

Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control.
CoRR, 2021

Boxhead: A Dataset for Learning Hierarchical Representations.
CoRR, 2021

A Robot Cluster for Reproducible Research in Dexterous Manipulation.
CoRR, 2021

Learning Neural Causal Models with Active Interventions.
CoRR, 2021

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning.
CoRR, 2021

Interventional Assays for the Latent Space of Autoencoders.
CoRR, 2021

Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics.
CoRR, 2021

Real-time gravitational-wave science with neural posterior estimation.
CoRR, 2021

Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects.
CoRR, 2021

Instrument Space Selection for Kernel Maximum Moment Restriction.
CoRR, 2021

Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases.
CoRR, 2021

A prior-based approximate latent Riemannian metric.
CoRR, 2021

Nonlinear Invariant Risk Minimization: A Causal Approach.
CoRR, 2021

Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners.
CoRR, 2021

Towards Causal Representation Learning.
CoRR, 2021

From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing.
CoRR, 2021

An Optimal Witness Function for Two-Sample Testing.
CoRR, 2021

Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study.
Comput. Medical Imaging Graph., 2021

Regret Bounds for Gaussian-Process Optimization in Large Domains.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Inference with Neural Interpreters.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DiBS: Differentiable Bayesian Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Iterative Teaching by Label Synthesis.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Independent mechanism analysis, a new concept?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Neural Lyapunov Redesign.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

On Disentangled Representations Learned from Correlated Data.
Proceedings of the 38th International Conference on Machine Learning, 2021

Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

Function Contrastive Learning of Transferable Meta-Representations.
Proceedings of the 38th International Conference on Machine Learning, 2021

Bayesian Quadrature on Riemannian Data Manifolds.
Proceedings of the 38th International Conference on Machine Learning, 2021

Spatially Structured Recurrent Modules.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning explanations that are hard to vary.
Proceedings of the 9th International Conference on Learning Representations, 2021

A teacher-student framework to distill future trajectories.
Proceedings of the 9th International Conference on Learning Representations, 2021

Fast And Slow Learning Of Recurrent Independent Mechanisms.
Proceedings of the 9th International Conference on Learning Representations, 2021

Recurrent Independent Mechanisms.
Proceedings of the 9th International Conference on Learning Representations, 2021

On the Transfer of Disentangled Representations in Realistic Settings.
Proceedings of the 9th International Conference on Learning Representations, 2021


CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Algorithmic Recourse: from Counterfactual Explanations to Interventions.
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.
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.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning with Hyperspherical Uniformity.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Geometrically Enriched Latent Spaces.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Theory of Independent Mechanisms for Extrapolation in Generative Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adaptation and Robust Learning of Probabilistic Movement Primitives.
IEEE Trans. Robotics, 2020

Real Time Trajectory Prediction Using Deep Conditional Generative Models.
IEEE Robotics Autom. Lett., 2020

A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation.
J. Mach. Learn. Res., 2020

Causal Discovery from Heterogeneous/Nonstationary Data.
J. Mach. Learn. Res., 2020

Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation.
CoRR, 2020

PanCast: Listening to Bluetooth Beacons for Epidemic Risk Mitigation.
CoRR, 2020

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.
CoRR, 2020

Maximum Moment Restriction for Instrumental Variable Regression.
CoRR, 2020

Function Contrastive Learning of Transferable Representations.
CoRR, 2020

Physically constrained causal noise models for high-contrast imaging of exoplanets.
CoRR, 2020

A survey of algorithmic recourse: definitions, formulations, solutions, and prospects.
CoRR, 2020

Real-time Prediction of COVID-19 related Mortality using Electronic Health Records.
CoRR, 2020

Learning Dynamical Systems using Local Stability Priors.
CoRR, 2020

TriFinger: An Open-Source Robot for Learning Dexterity.
CoRR, 2020

Bloom Origami Assays: Practical Group Testing.
CoRR, 2020

S2RMs: Spatially Structured Recurrent Modules.
CoRR, 2020

Is Independence all you need? On the Generalization of Representations Learned from Correlated Data.
CoRR, 2020

Structural Autoencoders Improve Representations for Generation and Transfer.
CoRR, 2020

Kernel Distributionally Robust Optimization.
CoRR, 2020

Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems.
CoRR, 2020

Crackovid: Optimizing Group Testing.
CoRR, 2020

Towards causal generative scene models via competition of experts.
CoRR, 2020

A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment.
CoRR, 2020

SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives.
CoRR, 2020

DeepMAsED: evaluating the quality of metagenomic assemblies.
Bioinform., 2020

MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware.
Proceedings of the UIST '20: The 33rd Annual ACM Symposium on User Interface Software and Technology, 2020

On the design of consequential ranking algorithms.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Semi-supervised learning, causality, and the conditional cluster assumption.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Testing Goodness of Fit of Conditional Density Models with Kernels.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Bayesian Online Prediction of Change Points.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Causal analysis of Covid-19 Spread in Germany.
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.
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.
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.
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.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Weakly-Supervised Disentanglement Without Compromises.
Proceedings of the 37th International Conference on Machine Learning, 2020

Towards Causal Algorithmic Recourse.
Proceedings of the xxAI - Beyond Explainable AI, 2020

Disentangling Factors of Variations Using Few Labels.
Proceedings of the 8th International Conference on Learning Representations, 2020

From Variational to Deterministic Autoencoders.
Proceedings of the 8th International Conference on Learning Representations, 2020

Counterfactuals uncover the modular structure of deep generative models.
Proceedings of the 8th International Conference on Learning Representations, 2020


Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Fair Decisions Despite Imperfect Predictions.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Commentary on the Unsupervised Learning of Disentangled Representations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reliable Real-Time Ball Tracking for Robot Table Tennis.
Robotics, 2019

Analysis of cause-effect inference by comparing regression errors.
PeerJ Comput. Sci., 2019

Data scarcity, robustness and extreme multi-label classification.
Mach. Learn., 2019

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.
J. Mach. Learn. Res., 2019

A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming.
CoRR, 2019

Causality for Machine Learning.
CoRR, 2019

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks.
CoRR, 2019

Disentangled State Space Representations.
CoRR, 2019

Quantum Mean Embedding of Probability Distributions.
CoRR, 2019

Optimal Decision Making Under Strategic Behavior.
CoRR, 2019

Consequential Ranking Algorithms and Long-term Welfare.
CoRR, 2019

Disentangling Factors of Variation Using Few Labels.
CoRR, 2019

Convolutional neural networks: a magic bullet for gravitational-wave detection?
CoRR, 2019

Bayesian Online Detection and Prediction of Change Points.
CoRR, 2019

Improving Consequential Decision Making under Imperfect Predictions.
CoRR, 2019

GeNet: Deep Representations for Metagenomics.
CoRR, 2019

Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces.
CoRR, 2019

Multidimensional Contrast Limited Adaptive Histogram Equalization.
IEEE Access, 2019

The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA.
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.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Neural Signatures of Motor Skill in the Resting Brain.
Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Perceiving the arrow of time in autoregressive motion.
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.
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.
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.
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.
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.
Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness.
Proceedings of the 36th International Conference on Machine Learning, 2019

First-Order Adversarial Vulnerability of Neural Networks and Input Dimension.
Proceedings of the 36th International Conference on Machine Learning, 2019

Kernel Mean Matching for Content Addressability of GANs.
Proceedings of the 36th International Conference on Machine Learning, 2019

AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.
Proceedings of the Reproducibility in Machine Learning, 2019

Learning causal mechanisms.
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.
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.
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.
IEEE Trans. Image Process., 2018

Control of Musculoskeletal Systems Using Learned Dynamics Models.
IEEE Robotics Autom. Lett., 2018

Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions.
J. Mach. Learn. Res., 2018

Invariant Models for Causal Transfer Learning.
J. Mach. Learn. Res., 2018

Deconfounding Reinforcement Learning in Observational Settings.
CoRR, 2018

Counterfactuals uncover the modular structure of deep generative models.
CoRR, 2018

Generalization in anti-causal learning.
CoRR, 2018

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.
CoRR, 2018

Deep Nonlinear Non-Gaussian Filtering for Dynamical Systems.
CoRR, 2018

Interventional Robustness of Deep Latent Variable Models.
CoRR, 2018

Photorealistic Video Super Resolution.
CoRR, 2018

groupICA: Independent component analysis for grouped data.
CoRR, 2018

A Local Information Criterion for Dynamical Systems.
CoRR, 2018

Minimum Information Exchange in Distributed Systems.
CoRR, 2018

Deep Energy Estimator Networks.
CoRR, 2018

Revisiting First-Order Convex Optimization Over Linear Spaces.
CoRR, 2018

Coordination via predictive assistants from a game-theoretic view.
CoRR, 2018

Adversarial Extreme Multi-label Classification.
CoRR, 2018

Analysis of Cause-Effect Inference via Regression Errors.
CoRR, 2018

Tempered Adversarial Networks.
CoRR, 2018

On the Latent Space of Wasserstein Auto-Encoders.
CoRR, 2018

Adversarial Vulnerability of Neural Networks Increases With Input Dimension.
CoRR, 2018

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

From Deterministic ODEs to Dynamic Structural Causal Models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Informative Features for Model Comparison.
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.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Learning Independent Causal Mechanisms.
Proceedings of the 35th International Conference on Machine Learning, 2018

On Matching Pursuit and Coordinate Descent.
Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting non-causal artifacts in multivariate linear regression models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Differentially Private Database Release via Kernel Mean Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Wasserstein Auto-Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Tempered Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Disentangled Representations with Wasserstein Auto-Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Clustering Meets Implicit Generative Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

Fidelity-Weighted Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Automatic estimation of modulation transfer functions.
Proceedings of the 2018 IEEE International Conference on Computational Photography, 2018

Spatio-Temporal Transformer Network for Video Restoration.
Proceedings of the Computer Vision - ECCV 2018, 2018

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Efficient Encoding of Dynamical Systems Through Local Approximations.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Cause-Effect Inference by Comparing Regression Errors.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Group invariance principles for causal generative models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
BundleMAP: Anatomically localized classification, regression, and hypothesis testing in diffusion MRI.
Pattern Recognit., 2017

Kernel Mean Embedding of Distributions: A Review and Beyond.
Found. Trends Mach. Learn., 2017

Optimizing Human Learning.
CoRR, 2017

Probabilistic Active Learning of Functions in Structural Causal Models.
CoRR, 2017

Annealed Generative Adversarial Networks.
CoRR, 2017

Discriminative k-shot learning using probabilistic models.
CoRR, 2017

Anticipatory action selection for human-robot table tennis.
Artif. Intell., 2017

Distilling Information Reliability and Source Trustworthiness from Digital Traces.
Proceedings of the 26th International Conference on World Wide Web, 2017

DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Causal Consistency of Structural Equation Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Causal Discovery from Temporally Aggregated Time Series.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Personalized brain-computer interface models for motor rehabilitation.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

AdaGAN: Boosting Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Avoiding Discrimination through Causal Reasoning.
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.
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.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Learning Blind Motion Deblurring.
Proceedings of the IEEE International Conference on Computer Vision, 2017

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Online Video Deblurring via Dynamic Temporal Blending Network.
Proceedings of the IEEE International Conference on Computer Vision, 2017

A Guided Task for Cognitive brain-Computer Interfaces.
Proceedings of the From Vision to Reality, 2017

Closing One's eyes Affects amplitude modulation but not frequency modulation in a Cognitive BCI.
Proceedings of the From Vision to Reality, 2017

Flexible Spatio-Temporal Networks for Video Prediction.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Discovering Causal Signals in Images.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Local Group Invariant Representations via Orbit Embeddings.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Influence Estimation and Maximization in Continuous-Time Diffusion Networks.
ACM Trans. Inf. Syst., 2016

On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model.
ACM Trans. Intell. Syst. Technol., 2016

Preface to the ACM TIST Special Issue on Causal Discovery and Inference.
ACM Trans. Intell. Syst. Technol., 2016

Gaussian Process-Based Predictive Control for Periodic Error Correction.
IEEE Trans. Control. Syst. Technol., 2016

Modeling confounding by half-sibling regression.
Proc. Natl. Acad. Sci. USA, 2016

Learning to Deblur.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach.
NeuroImage, 2016

Kernel Mean Shrinkage Estimators.
J. Mach. Learn. Res., 2016

Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks.
J. Mach. Learn. Res., 2016

Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm.
J. Mach. Learn. Res., 2016

New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481).
Dagstuhl Reports, 2016

Optimal Coding in Biological and Artificial Neural Networks.
CoRR, 2016

Screening Rules for Convex Problems.
CoRR, 2016

Kernel Mean Embedding of Distributions: A Review and Beyonds.
CoRR, 2016

Unifying distillation and privileged information.
Proceedings of the 4th International Conference on Learning Representations, 2016

Experimental and causal view on information integration in autonomous agents.
CoRR, 2016

Causal models for debugging and control in cloud computing.
CoRR, 2016

Structural Causal Models: Cycles, Marginalizations, Exogenous Reparametrizations and Reductions.
CoRR, 2016

Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail.
IEEE Comput. Intell. Mag., 2016

On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels.
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.
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.
Proceedings of the 33nd International Conference on Machine Learning, 2016

The Arrow of Time in Multivariate Time Series.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Jointly learning trajectory generation and hitting point prediction in robot table tennis.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Using probabilistic movement primitives for striking movements.
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.
Proceedings of the 15th European Control Conference, 2016

Depth Estimation Through a Generative Model of Light Field Synthesis.
Proceedings of the Pattern Recognition - 38th German Conference, 2016

End-to-End Learning for Image Burst Deblurring.
Proceedings of the Computer Vision - ACCV 2016, 2016

2015
Computing functions of random variables via reproducing kernel Hilbert space representations.
Stat. Comput., 2015

Causal interpretation rules for encoding and decoding models in neuroimaging.
NeuroImage, 2015

Artificial intelligence: Learning to see and act.
Nat., 2015

Semi-supervised interpolation in an anticausal learning scenario.
J. Mach. Learn. Res., 2015

Distinguishing Cause from Effect Based on Exogeneity.
CoRR, 2015

Towards Robust and Specific Causal Discovery from fMRI.
CoRR, 2015

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations.
CoRR, 2015

Transfer Learning in Brain-Computer Interfaces.
CoRR, 2015

A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015

Learning optimal striking points for a ping-pong playing robot.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Identification of Time-Dependent Causal Model: A Gaussian Process Treatment.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Telling cause from effect in deterministic linear dynamical systems.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Removing systematic errors for exoplanet search via latent causes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Towards a Learning Theory of Cause-Effect Inference.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Retrospective Motion Correction of Magnitude-Input MR Images.
Proceedings of the Machine Learning Meets Medical Imaging - First International Workshop, 2015

Discovering Temporal Causal Relations from Subsampled Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Self-Calibration of Optical Lenses.
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.
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.
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.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Multi-Source Domain Adaptation: A Causal View.
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.
IEEE Trans. Geosci. Remote. Sens., 2014

Uncovering the structure and temporal dynamics of information propagation.
Netw. Sci., 2014

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings.
Neural Comput., 2014

Causal discovery with continuous additive noise models.
J. Mach. Learn. Res., 2014

Learning strategies in table tennis using inverse reinforcement learning.
Biol. Cybern., 2014

Estimating Causal Effects by Bounding Confounding.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

A Permutation-Based Kernel Conditional Independence Test.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Inferring latent structures via information inequalities.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Causal and anti-causal learning in pattern recognition for neuroimaging.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Kernel Mean Estimation via Spectral Filtering.
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.
Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

Kernel Mean Estimation and Stein Effect.
Proceedings of the 31th International Conference on Machine Learning, 2014

Randomized Nonlinear Component Analysis.
Proceedings of the 31th International Conference on Machine Learning, 2014

Consistency of Causal Inference under the Additive Noise Model.
Proceedings of the 31th International Conference on Machine Learning, 2014

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm.
Proceedings of the 31th International Conference on Machine Learning, 2014

Mask-Specific Inpainting with Deep Neural Networks.
Proceedings of the Pattern Recognition - 36th German Conference, 2014

Seeing the Arrow of Time.
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.
Proceedings of The 27th Conference on Learning Theory, 2014

Decoding index finger position from EEG using random forests.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

Towards building a Crowd-Sourced Sky Map.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Probabilistic movement modeling for intention inference in human-robot interaction.
Int. J. Robotics Res., 2013

Kernel Mean Estimation and Stein's Effect.
CoRR, 2013

HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization.
Comput. Graph. Forum, 2013

Structure and dynamics of information pathways in online media.
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.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

One-Class Support Measure Machines for Group Anomaly Detection.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

From Ordinary Differential Equations to Structural Causal Models: the deterministic case.
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.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Causal Inference on Time Series using Restricted Structural Equation Models.
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.
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.
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.
Proceedings of the 30th International Conference on Machine Learning, 2013

Domain Generalization via Invariant Feature Representation.
Proceedings of the 30th International Conference on Machine Learning, 2013

Modeling Information Propagation with Survival Theory.
Proceedings of the 30th International Conference on Machine Learning, 2013

Improving alpha matting and motion blurred foreground estimation.
Proceedings of the IEEE International Conference on Image Processing, 2013

On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

A Machine Learning Approach for Non-blind Image Deconvolution.
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.
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.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Semi-supervised Learning in Causal and Anticausal Settings.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Nonparametric dynamics estimation for time periodic systems.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
A Kernel Two-Sample Test.
J. Mach. Learn. Res., 2012

easyGWAS: An integrated interspecies platform for performing genome-wide association studies
CoRR, 2012

Causal Inference on Time Series using Structural Equation Models
CoRR, 2012

Information-geometric approach to inferring causal directions.
Artif. Intell., 2012

Probabilistic Modeling of Human Movements for Intention Inference.
Proceedings of the Robotics: Science and Systems VIII, 2012

Learning from Distributions via Support Measure Machines.
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.
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.
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.
Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

On causal and anticausal learning.
Proceedings of the 29th International Conference on Machine Learning, 2012

Submodular Inference of Diffusion Networks from Multiple Trees.
Proceedings of the 29th International Conference on Machine Learning, 2012

Influence Maximization in Continuous Time Diffusion Networks.
Proceedings of the 29th International Conference on Machine Learning, 2012

A blind deconvolution approach for pseudo CT prediction from MR image pairs.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Blind Correction of Optical Aberrations.
Proceedings of the Computer Vision - ECCV 2012, 2012

Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Statistical Learning Theory: Models, Concepts, and Results.
Proceedings of the Inductive Logic, 2011

Causal Inference on Discrete Data Using Additive Noise Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

Causal influence of gamma oscillations on the sensorimotor rhythm.
NeuroImage, 2011

A Graphical Model Framework for Decoding in the Visual ERP-Based BCI Speller.
Neural Comput., 2011

Multi-way set enumeration in weight tensors.
Mach. Learn., 2011

A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps.
J. Comput. Biol., 2011

Robust Learning via Cause-Effect Models
CoRR, 2011

Kernel-based Conditional Independence Test and Application in Causal Discovery.
Proceedings of the UAI 2011, 2011

Identifiability of Causal Graphs using Functional Models.
Proceedings of the UAI 2011, 2011

Detecting low-complexity unobserved causes.
Proceedings of the UAI 2011, 2011

On Causal Discovery with Cyclic Additive Noise Models.
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.
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.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Learning anticipation policies for robot table tennis.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Learning inverse kinematics with structured prediction.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Uncovering the Temporal Dynamics of Diffusion Networks.
Proceedings of the 28th International Conference on Machine Learning, 2011

Support Vector Machines as Probabilistic Models.
Proceedings of the 28th International Conference on Machine Learning, 2011

Non-stationary correction of optical aberrations.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Fast removal of non-uniform camera shake.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Removing noise from astronomical images using a pixel-specific noise model.
Proceedings of the 2011 IEEE International Conference on Computational Photography, 2011

Finding dependencies between frequencies with the kernel cross-spectral density.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Causal inference using the algorithmic Markov condition.
IEEE Trans. Inf. Theory, 2010

Nonparametric Regression between General Riemannian Manifolds.
SIAM J. Imaging Sci., 2010

Remote Sensing Feature Selection by Kernel Dependence Measures.
IEEE Geosci. Remote. Sens. Lett., 2010

Hilbert Space Embeddings and Metrics on Probability Measures.
J. Mach. Learn. Res., 2010

Identifying Cause and Effect on Discrete Data using Additive Noise Models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Causality: Objectives and Assessment.
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.
J. Comput. Neurosci., 2010

Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery.
Proceedings of the UAI 2010, 2010

Inferring deterministic causal relations.
Proceedings of the UAI 2010, 2010

Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery.
Proceedings of the IEEE International Conference on Systems, 2010

A New Algorithm for Improving the Resolution of Cryo-EM Density Maps.
Proceedings of the Research in Computational Molecular Biology, 2010

Probabilistic latent variable models for distinguishing between cause and effect.
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.
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.
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.
Proceedings of the IEEE International Symposium on Information Theory, 2010

The Influence of the Image Basis on Modeling and Steganalysis Performance.
Proceedings of the Information Hiding - 12th International Conference, 2010

Movement templates for learning of hitting and batting.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Telling cause from effect based on high-dimensional observations.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM.
Proceedings of the International Conference on Image Processing, 2010

Efficient filter flow for space-variant multiframe blind deconvolution.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Causal Markov Condition for Submodular Information Measures.
Proceedings of the COLT 2010, 2010

2009
Prototype Classification: Insights from Machine Learning.
Neural Comput., 2009

Protein functional class prediction with a combined graph.
Expert Syst. Appl., 2009

A note on integral probability metrics and $\phi$-divergences
CoRR, 2009

Identifying confounders using additive noise models.
Proceedings of the UAI 2009, 2009

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions.
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.
Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

Multi-way set enumeration in real-valued tensors.
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.
Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Detecting the direction of causal time series.
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.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

09401 Abstracts Collection - Machine learning approaches to statistical dependences and causality.
Proceedings of the Machine learning approaches to statistical dependences and causality, 27.09., 2009

Markerless 3D Face Tracking.
Proceedings of the Pattern Recognition, 2009

Learning similarity measure for multi-modal 3D image registration.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Kernels, regularization and differential equations.
Pattern Recognit., 2008

Support Vector Machines and Kernels for Computational Biology.
PLoS Comput. Biol., 2008

Causal reasoning by evaluating the complexity of conditional densities with kernel methods.
Neurocomputing, 2008

Guest Editorial.
Int. J. Comput. Vis., 2008

Manifold-valued Thin-Plate Splines with Applications in Computer Graphics.
Comput. Graph. Forum, 2008

Diffeomorphic Dimensionality Reduction.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Bayesian Experimental Design of Magnetic Resonance Imaging Sequences.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Nonlinear causal discovery with additive noise models.
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.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Characteristic Kernels on Groups and Semigroups.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Sparse multiscale gaussian process regression.
Proceedings of the Machine Learning, 2008

Tailoring density estimation via reproducing kernel moment matching.
Proceedings of the Machine Learning, 2008

Kernel Methods for Detecting the Direction of Time Series.
Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008

Automatic 3D face reconstruction from single images or video.
Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

Learning Inverse Dynamics: a Comparison.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

Automatic Image Colorization Via Multimodal Predictions.
Proceedings of the Computer Vision, 2008

Injective Hilbert Space Embeddings of Probability Measures.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA.
IEEE Trans. Biomed. Eng., 2007

Feature Selection for Troubleshooting in Complex Assembly Lines.
IEEE Trans Autom. Sci. Eng., 2007

Improving the <i>Caenorhabditis elegans</i> Genome Annotation Using Machine Learning.
PLoS Comput. Biol., 2007

Transductive Classification via Local Learning Regularization.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

The Need for Open Source Software in Machine Learning.
J. Mach. Learn. Res., 2007

An Analysis of Inference with the Universum.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Kernel Statistical Test of Independence.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Kernel Measures of Conditional Dependence.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Local learning projections.
Proceedings of the Machine Learning, 2007

A kernel-based causal learning algorithm.
Proceedings of the Machine Learning, 2007

Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

A Hilbert Space Embedding for Distributions.
Proceedings of the Discovery Science, 10th International Conference, 2007

How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements.
Proceedings of the Pattern Recognition, 2007

Towards Machine Learning of Motor Skills.
Proceedings of the Autonome Mobile Systeme 2007, 2007

A Kernel Approach to Comparing Distributions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Classification of Faces in Man and Machine.
Neural Comput., 2006

A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression.
Neural Comput., 2006

A Direct Method for Building Sparse Kernel Learning Algorithms.
J. Mach. Learn. Res., 2006

Large Scale Multiple Kernel Learning.
J. Mach. Learn. Res., 2006

Implicit Surface Modelling with a Globally Regularised Basis of Compact Support.
Comput. Graph. Forum, 2006

Learning with Hypergraphs: Clustering, Classification, and Embedding.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Local Learning Approach for Clustering.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Learning Dense 3D Correspondence.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Nonparametric Approach to Bottom-Up Visual Saliency.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Correcting Sample Selection Bias by Unlabeled Data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Integrating structured biological data by Kernel Maximum Mean Discrepancy.
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.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals.
Proceedings of the Pattern Recognition, 2006

Learning an Interest Operator from Human Eye Movements.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

Combining a Filter Method with SVMs.
Proceedings of the Feature Extraction - Foundations and Applications, 2006

Discrete Regularization.
Proceedings of the Semi-Supervised Learning, 2006

A Discussion of Semi-Supervised Learning and Transduction.
Proceedings of the Semi-Supervised Learning, 2006

Analysis of Benchmarks.
Proceedings of the Semi-Supervised Learning, 2006

Introduction to Semi-Supervised Learning.
Proceedings of the Semi-Supervised Learning, 2006

2005
Iterative Kernel Principal Component Analysis for Image Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., 2005

Experimentally optimal nu in support vector regression for different noise models and parameter settings.
Neural Networks, 2005

Kernel Methods for Measuring Independence.
J. Mach. Learn. Res., 2005

Maximal margin classification for metric spaces.
J. Comput. Syst. Sci., 2005

Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces.
EURASIP J. Adv. Signal Process., 2005

Support Vector Machines for 3D Shape Processing.
Comput. Graph. Forum, 2005

Evaluating Predictive Uncertainty Challenge.
Proceedings of the Machine Learning Challenges, 2005

Joint Kernel Maps.
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.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

RASE: recognition of alternatively spliced exons in <i>C.elegans</i>.
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.
Proceedings of the Machine Learning, 2005

Building Sparse Large Margin Classifiers.
Proceedings of the Machine Learning, 2005

Implicit surface modelling as an eigenvalue problem.
Proceedings of the Machine Learning, 2005

Large scale genomic sequence SVM classifiers.
Proceedings of the Machine Learning, 2005

Object correspondence as a machine learning problem.
Proceedings of the Machine Learning, 2005

A brain computer interface with online feedback based on magnetoencephalography.
Proceedings of the Machine Learning, 2005

Training Support Vector Machines with Multiple Equality Constraints.
Proceedings of the Machine Learning: ECML 2005, 2005

Fast protein classification with multiple networks.
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.
Proceedings of the Pattern Recognition, 27th DAGM Symposium, Vienna, Austria, August 31, 2005

Measuring Statistical Dependence with Hilbert-Schmidt Norms.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Kernel Constrained Covariance for Dependence Measurement.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Support vector channel selection in BCI.
IEEE Trans. Biomed. Eng., 2004

A tutorial on support vector regression.
Stat. Comput., 2004

Experimentally optimal v in support vector regression for different noise models and parameter settings.
Neural Networks, 2004

A Compression Approach to Support Vector Model Selection.
J. Mach. Learn. Res., 2004

Feature Selection for Support Vector Machines Using Genetic Algorithms.
Int. J. Artif. Intell. Tools, 2004

Semi-supervised Learning on Directed Graphs.
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.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Kernel Methods for Implicit Surface Modeling.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Methods Towards Invasive Human Brain Computer Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Face Detection - Efficient and Rank Deficient.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

An Auditory Paradigm for Brain-Computer Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Implicit Wiener Series for Higher-Order Image Analysis.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A kernel view of the dimensionality reduction of manifolds.
Proceedings of the Machine Learning, 2004

Learning from Labeled and Unlabeled Data Using Random Walks.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Efficient Approximations for Support Vector Machines in Object Detection.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Semi-supervised Kernel Regression Using Whitened Function Classes.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Multivariate Regression via Stiefel Manifold Constraints.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

2003
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Use of the Zero-Norm with Linear Models and Kernel Methods.
J. Mach. Learn. Res., 2003

Statistical learning theory, capacity, and complexity.
Complex., 2003

Feature selection and transduction for prediction of molecular bioactivity for drug design.
Bioinform., 2003

Ranking on Data Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning with Local and Global Consistency.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Prediction on Spike Data Using Kernel Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning to Find Pre-Images.
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.
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.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Training Invariant Support Vector Machines.
Mach. Learn., 2002

Support Vector Machines and Kernel Methods: The New Generation of Learning Machines.
AI Mag., 2002

A Kernel Approach for Learning from Almost Orthogonal Patterns.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

Kernel Dependency Estimation.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Cluster Kernels for Semi-Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Bayesian Kernel Methods.
Proceedings of the Advanced Lectures on Machine Learning, 2002

A Short Introduction to Learning with Kernels.
Proceedings of the Advanced Lectures on Machine Learning, 2002

Learning with Kernels: support vector machines, regularization, optimization, and beyond.
Adaptive computation and machine learning series, MIT Press, ISBN: 9780262194754, 2002

2001
An introduction to kernel-based learning algorithms.
IEEE Trans. Neural Networks, 2001

Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators.
IEEE Trans. Inf. Theory, 2001

Estimating the Support of a High-Dimensional Distribution.
Neural Comput., 2001

Regularized Principal Manifolds.
J. Mach. Learn. Res., 2001

Incorporating Invariances in Non-Linear Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Sampling Techniques for Kernel Methods.
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.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

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

A Generalized Representer Theorem.
Proceedings of the Computational Learning Theory, 2001

A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

An improved training algorithm for kernel Fisher discriminants.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

Statistical Learning and Kernel Methods.
Proceedings of the Data Fusion and Perception, 2001

2000
New Support Vector Algorithms.
Neural Comput., 2000

Engineering support vector machine kernels that recognize translation initiation sites.
Bioinform., 2000

Robust Ensemble Learning for Data Mining.
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.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

The Kernel Trick for Distances.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Sparse Greedy Matrix Approximation for Machine Learning.
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.
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.
IEEE Trans. Neural Networks, 1999

Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten.
Inform. Forsch. Entwickl., 1999

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

Support Vector Method for Novelty Detection.
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.
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.
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.
Proceedings of the German Conference on Bioinformatics, 1999

Entropy Numbers, Operators and Support Vector Kernels.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

1998
The connection between regularization operators and support vector kernels.
Neural Networks, 1998

Nonlinear Component Analysis as a Kernel Eigenvalue Problem.
Neural Comput., 1998

Where did I take that snapshot? Scene-based homing by image matching.
Biol. Cybern., 1998

Learning View Graphs for Robot Navigation.
Auton. Robots, 1998

On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion.
Algorithmica, 1998

Semiparametric Support Vector and Linear Programming Machines.
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.
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.
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.
Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

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

1997
Support vector learning.
PhD thesis, 1997

Comparing support vector machines with Gaussian kernels to radial basis function classifiers.
IEEE Trans. Signal Process., 1997

From Regularization Operators to Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Prior Knowledge in Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Kernel Principal Component Analysis.
Proceedings of the Artificial Neural Networks, 1997

Predicting Time Series with Support Vector Machines.
Proceedings of the Artificial Neural Networks, 1997

The View-Graph Approach to Visual Navigation and Spatial Memory.
Proceedings of the Artificial Neural Networks, 1997

Learning View Graphs for Robot Navigation.
Proceedings of the First International Conference on Autonomous Agents, 1997

1996
Improving the Accuracy and Speed of Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Incorporating Invariances in Support Vector Learning Machines.
Proceedings of the Artificial Neural Networks, 1996

Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models.
Proceedings of the Artificial Neural Networks, 1996

1995
View-Based Cognitive Mapping and Path Planning.
Adapt. Behav., 1995

Extracting Support Data for a Given Task.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995


  Loading...