Schölkopf, Bernhard

410 publications

AISTATS 2025 Accuracy on the Wrong Line: On the Pitfalls of Noisy Data for Out-of-Distribution Generalisation Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf
CLeaR 2025 Algorithmic Causal Structure Emerging Through Compression Liang Wendong, Simon Buchholz, Bernhard Schölkopf
NeurIPS 2025 Are Language Models Efficient Reasoners? a Perspective from Logic Programming Andreas Opedal, Yanick Zengaffinen, Haruki Shirakami, Clemente Pasti, Mrinmaya Sachan, Abulhair Saparov, Ryan Cotterell, Bernhard Schölkopf
ICLR 2025 Can Large Language Models Understand Symbolic Graphics Programs? Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf
ICLR 2025 Conformal Generative Modeling with Improved Sample Efficiency Through Sequential Greedy Filtering Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
NeurIPS 2025 Counterfactual Reasoning: An Analysis of In-Context Emergence Moritz Miller, Bernhard Schölkopf, Siyuan Guo
NeurIPS 2025 Do-PFN: In-Context Learning for Causal Effect Estimation Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf
ICML 2025 Generalized Interpolating Discrete Diffusion Dimitri Von Rütte, Janis Fluri, Yuhui Ding, Antonio Orvieto, Bernhard Schölkopf, Thomas Hofmann
ICML 2025 Generative Intervention Models for Causal Perturbation Modeling Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
ICLR 2025 Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
ICLR 2025 Language Model Alignment in Multilingual Trolley Problems Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf
ICML 2025 Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models Armin Kekić, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
ICLR 2025 MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
ICLR 2025 Preference Elicitation for Offline Reinforcement Learning Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch, Giorgia Ramponi
NeurIPS 2025 Reparameterized LLM Training via Orthogonal Equivalence Transformation Zeju Qiu, Simon Buchholz, Tim Z. Xiao, Maximilian Dax, Bernhard Schölkopf, Weiyang Liu
NeurIPS 2025 SPARTAN: A Sparse Transformer World Model Attending to What Matters Anson Lei, Bernhard Schölkopf, Ingmar Posner
ICLR 2025 Standardizing Structural Causal Models Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
ICLR 2025 The Directionality of Optimization Trajectories in Neural Networks Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf
ICLRW 2025 Towards Training One-Step Diffusion Models Without Distillation Mingtian Zhang, Jiajun He, Wenlin Chen, Zijing Ou, José Miguel Hernández-Lobato, Bernhard Schölkopf, David Barber
ICLRW 2025 Unifying Causal and Object-Centric Representation Learning Allows Causal Composition Avinash Kori, Ben Glocker, Bernhard Schölkopf, Francesco Locatello
TMLR 2025 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
TMLR 2024 A Probabilistic Model Behind Self- Supervised Learning Alice Bizeul, Bernhard Schölkopf, Carl Allen
ICMLW 2024 Accuracy on the Wrong Line: On the Pitfalls of Noisy Data for OOD Generalisation Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf
NeurIPSW 2024 Analyzing Human Questioning Behavior and Causal Curiosity Through Natural Queries Roberto Ceraolo, Dmitrii Kharlapenko, Amélie Reymond, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan, Zhijing Jin
ICLR 2024 Can Large Language Models Infer Causation from Correlation? Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf
AISTATS 2024 Causal Modeling with Stationary Diffusions Lars Lorch, Andreas Krause, Bernhard Schölkopf
NeurIPS 2024 Causal vs. Anticausal Merging of Predictors Sergio Hernan Garrido Mejia, Patrick Blöbaum, Bernhard Schölkopf, Dominik Janzing
NeurIPS 2024 Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea
TMLR 2024 Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
ICLR 2024 Delphic Offline Reinforcement Learning Under Nonidentifiable Hidden Confounding Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Ratsch, Guy Tennenholtz
ICML 2024 Detecting and Identifying Selection Structure in Sequential Data Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang
NeurIPS 2024 Do Finetti: On Causal Effects for Exchangeable Data Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf
ICML 2024 Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
NeurIPSW 2024 Estimating Effects of Tokens in Preference Learning Hsiao-Ru Pan, Maximilian Mordig, Bernhard Schölkopf
NeurIPSW 2024 Estimating Effects of Tokens in Preference Learning Hsiao-Ru Pan, Maximilian Mordig, Bernhard Schölkopf
NeurIPS 2024 From Causal to Concept-Based Representation Learning Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
NeurIPSW 2024 From Causal to Concept-Based Representation Learning Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar
ICML 2024 Geometry-Aware Instrumental Variable Regression Heiner Kremer, Bernhard Schölkopf
ICLR 2024 Ghost on the Shell: An Expressive Representation of General 3D Shapes Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
CVPR 2024 GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf
ICMLW 2024 Hallmarks of Optimization Trajectories in Neural Networks and LLMs: Directional Exploration and Redundancy Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf
ICLR 2024 Identifying Policy Gradient Subspaces Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel Haeufle, Bernhard Schölkopf, Dieter Büchler
ICMLW 2024 Landscaping Linear Mode Connectivity Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann
NeurIPSW 2024 Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models Armin Kekić, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
NeurIPS 2024 Limits of Transformer Language Models on Learning to Compose Algorithms Jonathan Thomm, Giacomo Camposampiero, Aleksandar Terzic, Michael Hersche, Bernhard Schölkopf, Abbas Rahimi
NeurIPSW 2024 Multilingual Trolley Problems for Language Models Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf
NeurIPS 2024 On Affine Homotopy Between Language Encoders Robin S. M. Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell
ICLR 2024 Out-of-Variable Generalisation for Discriminative Models Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf
ICLR 2024 Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf
ICMLW 2024 Preference Elicitation for Offline Reinforcement Learning Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch, Giorgia Ramponi
ICMLW 2024 Preference Elicitation for Offline Reinforcement Learning Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch, Giorgia Ramponi
UAI 2024 Products, Abstractions and Inclusions of Causal Spaces Simon Buchholz, Junhyung Park, Bernhard Schölkopf
ICML 2024 Provable Privacy with Non-Private Pre-Processing Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
CoRL 2024 RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands Yi Zhao, Le Chen, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler
ICML 2024 Robustness of Nonlinear Representation Learning Simon Buchholz, Bernhard Schölkopf
ICLR 2024 Skill or Luck? Return Decomposition via Advantage Functions Hsiao-Ru Pan, Bernhard Schölkopf
ICMLW 2024 Stitching Manifolds: Leveraging Interaction to Compose Object Representations into Scenes. Hamza Keurti, Bernhard Schölkopf, Pau Vilimelis Aceituno, Benjamin F Grewe
UAI 2024 Targeted Reduction of Causal Models Armin Kekić, Bernhard Schölkopf, Michel Besserve
ICLRW 2024 Targeted Reduction of Causal Models Armin Kekić, Bernhard Schölkopf, Michel Besserve
ICLR 2024 The Expressive Leaky Memory Neuron: An Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina
TMLR 2024 Towards Fully Covariant Machine Learning Soledad Villar, David W Hogg, Weichi Yao, George A Kevrekidis, Bernhard Schölkopf
NeurIPSW 2024 Universal Approximation Capabilities of Coherent Diffractive Systems Lennart Schlieder, Valentin Volchkov, Alexander Song, Peer Fischer, Bernhard Schölkopf
NeurIPSW 2024 Unsupervised Causal Abstraction Yuchen Zhu, Sergio Hernan Garrido Mejia, Bernhard Schölkopf, Michel Besserve
ICMLW 2024 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
ICMLW 2024 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
NeurIPS 2023 A Measure-Theoretic Axiomatisation of Causality Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
AISTATS 2023 BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
ICLR 2023 Benchmarking Offline Reinforcement Learning on Real-Robot Hardware Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius
ICLR 2023 Bridging the Gap to Real-World Object-Centric Learning Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
NeurIPS 2023 CLadder: Assessing Causal Reasoning in Language Models Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
NeurIPS 2023 Causal Component Analysis Liang Wendong, Armin Kekić, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
NeurIPS 2023 Causal De Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data Siyuan Guo, Viktor Toth, Bernhard Schölkopf, Ferenc Huszar
UAI 2023 Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators Klaus-Rudolf Kladny, Julius Kügelgen, Bernhard Schölkopf, Michael Muehlebach
NeurIPSW 2023 Causal Modeling with Stationary Diffusions Lars Lorch, Andreas Krause, Bernhard Schölkopf
CLeaR 2023 Causal Triplet: An Open Challenge for Intervention-Centric Causal Representation Learning Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
NeurIPS 2023 Controlling Text-to-Image Diffusion by Orthogonal Finetuning Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
ICLR 2023 DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability Cian Eastwood, Andrei Liviu Nicolicioiu, Julius Von Kügelgen, Armin Kekić, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
ICMLW 2023 Delphic Offline Reinforcement Learning Under Nonidentifiable Hidden Confounding Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Ratsch, Guy Tennenholtz
ICMLW 2023 Desiderata for Representation Learning from Identifiability, Disentanglement, and Group-Structuredness Hamza Keurti, Patrik Reizinger, Bernhard Schölkopf, Wieland Brendel
ICML 2023 Diffusion Based Representation Learning Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
ICML 2023 Discrete Key-Value Bottleneck Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
ICML 2023 Estimation Beyond Data Reweighting: Kernel Method of Moments Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
ICLR 2023 Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato
NeurIPS 2023 Flow Matching for Scalable Simulation-Based Inference Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen Green, Jakob H Macke, Bernhard Schölkopf
ICMLW 2023 Flow Matching for Scalable Simulation-Based Inference Jonas Bernhard Wildberger, Maximilian Dax, Simon Buchholz, Stephen R Green, Jakob H. Macke, Bernhard Schölkopf
ICLR 2023 Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
ICML 2023 Homomorphism AutoEncoder -- Learning Group Structured Representations from Observed Transitions Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F Grewe, Bernhard Schölkopf
NeurIPSW 2023 Independent Mechanism Analysis and the Manifold Hypothesis Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf
AISTATS 2023 Iterative Teaching by Data Hallucination Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf
TMLR 2023 Jacobian-Based Causal Discovery with Nonlinear ICA Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
NeurIPSW 2023 Learning Endogenous Representation in Reinforcement Learning via Advantage Estimation Hsiao-Ru Pan, Bernhard Schölkopf
NeurIPS 2023 Learning Linear Causal Representations from Interventions Under General Nonlinear Mixing Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep K. Ravikumar
ICMLW 2023 Learning Linear Causal Representations from Interventions Under General Nonlinear Mixing Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar
L4DC 2023 Learning Locomotion Skills from MPC in Sensor Space Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf
NeurIPS 2023 Leveraging Sparse and Shared Feature Activations for Disentangled Representation Learning Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
JMLR 2023 Metrizing Weak Convergence with Maximum Mean Discrepancies Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey
TMLR 2023 Neural Causal Structure Discovery from Interventions Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
NeurIPS 2023 Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen, Michel Besserve, Liang Wendong, Luigi Gresele, Armin Kekić, Elias Bareinboim, David M. Blei, Bernhard Schölkopf
ICML 2023 On Data Manifolds Entailed by Structural Causal Models Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
ICML 2023 On the Identifiability and Estimation of Causal Location-Scale Noise Models Alexander Immer, Christoph Schultheiss, Julia E Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
CLeaR 2023 On the Interventional Kullback-Leibler Divergence Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
ICML 2023 On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
NeurIPSW 2023 On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
ICCV 2023 Pairwise Similarity Learning Is SimPLE Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
ICML 2023 Provably Learning Object-Centric Representations Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius Von Kügelgen, Wieland Brendel
NeurIPS 2023 SE(3) Equivariant Augmented Coupling Flows Laurence Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
NeurIPSW 2023 SE(3) Equivariant Augmented Coupling Flows Laurence Illing Midgley, Vincent Stimper, Javier Antoran, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
NeurIPSW 2023 Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Mark Ibrahim, Bernhard Schölkopf
NeurIPS 2023 Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features Cian Eastwood, Shashank Singh, Andrei L Nicolicioiu, Marin Vlastelica Pogančić, Julius von Kügelgen, Bernhard Schölkopf
ICML 2023 Stochastic Marginal Likelihood Gradients Using Neural Tangent Kernels Alexander Immer, Tycho F. A. Van Der Ouderaa, Mark Van Der Wilk, Gunnar Ratsch, Bernhard Schölkopf
ICLR 2023 Structure by Architecture: Structured Representations Without Regularization Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf
ICML 2023 The Hessian Perspective into the Nature of Convolutional Neural Networks Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf
CLeaR 2023 Unsupervised Object Learning via Common Fate Matthias Tangemann, Steffen Schneider, Julius Von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kuemmerer, Matthias Bethge, Bernhard Schölkopf
TMLR 2023 Variational Causal Dynamics: Discovering Modular World Models from Interventions Anson Lei, Bernhard Schölkopf, Ingmar Posner
AISTATS 2022 A Prior-Based Approximate Latent Riemannian Metric Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf
AISTATS 2022 A Witness Two-Sample Test Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
AISTATS 2022 Adversarially Robust Kernel Smoothing Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schölkopf
AISTATS 2022 GalilAI: Out-of-Task Distribution Detection Using Causal Active Experimentation for Safe Transfer RL Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
AISTATS 2022 Resampling Base Distributions of Normalizing Flows Vincent Stimper, Bernhard Schölkopf, Jose Miguel Hernandez-Lobato
ICML 2022 Action-Sufficient State Representation Learning for Control with Structural Constraints Biwei Huang, Chaochao Lu, Liu Leqi, Jose Miguel Hernandez-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
ICLRW 2022 Action-Sufficient State Representation Learning for Control with Structural Constraints Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
ICLR 2022 Adversarial Robustness Through the Lens of Causality Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
NeurIPS 2022 Amortized Inference for Causal Structure Learning Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
NeurIPSW 2022 Amortized Inference for Causal Structure Learning Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
NeurIPS 2022 Assaying Out-of-Distribution Generalization in Transfer Learning Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
NeurIPS 2022 AutoML Two-Sample Test Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
NeurIPSW 2022 Causal Discovery for Modular World Models Anson Lei, Bernhard Schölkopf, Ingmar Posner
NeurIPS 2022 Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf
TMLR 2022 Causal Feature Selection via Orthogonal Search Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve
ICML 2022 Causal Inference Through the Structural Causal Marginal Problem Luigi Gresele, Julius Von Kügelgen, Jonas Kübler, Elke Kirschbaum, Bernhard Schölkopf, Dominik Janzing
CLeaR 2022 Cause-Effect Inference Through Spectral Independence in Linear Dynamical Systems: Theoretical Foundations Michel Besserve, Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf
ICLRW 2022 Compositional Multi-Object Reinforcement Learning with Linear Relation Networks Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello
NeurIPS 2022 Direct Advantage Estimation Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf
NeurIPS 2022 Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
NeurIPSW 2022 Evaluating Vaccine Allocation Strategies Using Simulation-Assisted Causal Modelling Armin Kekić, Jonas Dehning, Luigi Gresele, Julius von Kügelgen, Viola Priesemann, Bernhard Schölkopf
NeurIPS 2022 Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf
NeurIPSW 2022 Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato
NeurIPS 2022 Function Classes for Identifiable Nonlinear Independent Component Analysis Simon Buchholz, Michel Besserve, Bernhard Schölkopf
ICML 2022 Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schölkopf
ICML 2022 Generalization and Robustness Implications in Object-Centric Learning Andrea Dittadi, Samuele S Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
ICLR 2022 Group Equivariant Neural Posterior Estimation Maximilian Dax, Stephen R Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke
NeurIPSW 2022 Homomorphism AutoEncoder --- Learning Group Structured Representations from Observed Transitions Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F Grewe, Bernhard Schölkopf
NeurIPS 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer
ICLRW 2022 Invariant Causal Representation Learning for Generalization in Imitation and Reinforcement Learning Chaochao Lu, José Miguel Hernández-Lobato, Bernhard Schölkopf
ICLR 2022 Invariant Causal Representation Learning for Out-of-Distribution Generalization Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf
UAI 2022 Learning Soft Interventions in Complex Equilibrium Systems Michel Besserve, Bernhard Schölkopf
CVPR 2022 Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
NeurIPS 2022 Neural Attentive Circuits Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Erran Li Li, Nicolas Ballas
ICML 2022 On the Adversarial Robustness of Causal Algorithmic Recourse Ricardo Dominguez-Olmedo, Amir H Karimi, Bernhard Schölkopf
AAAI 2022 On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf
ICLR 2022 Phenomenology of Double Descent in Finite-Width Neural Networks Sidak Pal Singh, Aurelien Lucchi, Thomas Hofmann, Bernhard Schölkopf
NeurIPS 2022 Probable Domain Generalization via Quantile Risk Minimization Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf
NeurIPS 2022 Sampling Without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization Aniket Das, Bernhard Schölkopf, Michael Muehlebach
ICML 2022 Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello
ICLR 2022 Source-Free Adaptation to Measurement Shift via Bottom-up Feature Restoration Cian Eastwood, Ian Mason, Chris Williams, Bernhard Schölkopf
ECCV 2022 Structural Causal 3D Reconstruction Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf
ICLR 2022 The Role of Pretrained Representations for the OOD Generalization of RL Agents Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
CVPR 2022 Towards Principled Disentanglement for Domain Generalization Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
CVPR 2022 Towards Total Recall in Industrial Anomaly Detection Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter Gehler
ICLR 2022 Visual Representation Learning Does Not Generalize Strongly Within the Same Domain Lukas Schott, Julius Von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
NeurIPS 2022 When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf
ICLR 2022 You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction Osama Makansi, Julius Von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
AISTATS 2021 Geometrically Enriched Latent Spaces Georgios Arvanitidis, Soren Hauberg, Bernhard Schölkopf
AISTATS 2021 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
AISTATS 2021 Learning with Hyperspherical Uniformity Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
ICLR 2021 A Teacher-Student Framework to Distill Future Trajectories Alexander Neitz, Giambattista Parascandolo, Bernhard Schölkopf
AAAI 2021 A Theory of Independent Mechanisms for Extrapolation in Generative Models Michel Besserve, Rémy Sun, Dominik Janzing, Bernhard Schölkopf
L4DC 2021 Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
NeurIPS 2021 Backward-Compatible Prediction Updates: A Probabilistic Approach Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler
ICML 2021 Bayesian Quadrature on Riemannian Data Manifolds Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
NeurIPSW 2021 Boxhead: A Dataset for Learning Hierarchical Representations Yukun Chen, Andrea Dittadi, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf
ICML 2021 Causal Curiosity: RL Agents Discovering Self-Supervised Experiments for Causal Representation Learning Sumedh A Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
NeurIPS 2021 Causal Influence Detection for Improving Efficiency in Reinforcement Learning Maximilian Seitzer, Bernhard Schölkopf, Georg Martius
ICLR 2021 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
ICML 2021 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet
NeurIPS 2021 DiBS: Differentiable Bayesian Structure Learning Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause
NeurIPS 2021 Dynamic Inference with Neural Interpreters Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
ICLR 2021 Fast and Slow Learning of Recurrent Independent Mechanisms Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
ICML 2021 Function Contrastive Learning of Transferable Meta-Representations Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf
NeurIPS 2021 Independent Mechanism Analysis, a New Concept? Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve
NeurIPS 2021 Iterative Teaching by Label Synthesis Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller
ICLR 2021 Learning Explanations That Are Hard to Vary Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf
ICML 2021 Necessary and Sufficient Conditions for Causal Feature Selection in Time Series with Latent Common Causes Atalanti A Mastakouri, Bernhard Schölkopf, Dominik Janzing
L4DC 2021 Neural Lyapunov Redesign Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
ICML 2021 On Disentangled Representations Learned from Correlated Data Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
ICLR 2021 On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
ICLR 2021 Predicting Infectiousness for Proactive Contact Tracing Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David Buckeridge, Gaetan Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz Gagne, Christopher Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
ICLR 2021 Recurrent Independent Mechanisms Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
NeurIPS 2021 Regret Bounds for Gaussian-Process Optimization in Large Domains Manuel Wuethrich, Bernhard Schölkopf, Andreas Krause
ICMLW 2021 Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
NeurIPS 2021 Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
ICLR 2021 Spatially Structured Recurrent Modules Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
NeurIPS 2021 The Inductive Bias of Quantum Kernels Jonas Kübler, Simon Buchholz, Bernhard Schölkopf
AAAI 2020 A Commentary on the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
JMLR 2020 A Sober Look at the Unsupervised Learning of Disentangled Representations and Their Evaluation Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
NeurIPS 2020 Algorithmic Recourse Under Imperfect Causal Knowledge: A Probabilistic Approach Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera
UAI 2020 Bayesian Online Prediction of Change Points Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters
NeurIPS 2020 Causal Analysis of Covid-19 Spread in Germany Atalanti Mastakouri, Bernhard Schölkopf
JMLR 2020 Causal Discovery from Heterogeneous/Nonstationary Data Biwei Huang, Kun Zhang, Jiji Zhang, Joseph Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
ICLR 2020 Counterfactuals Uncover the Modular Structure of Deep Generative Models Michel Besserve, Arash Mehrjou, Rémy Sun, Bernhard Schölkopf
ICLR 2020 Disentangling Factors of Variations Using Few Labels Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
AISTATS 2020 Fair Decisions Despite Imperfect Predictions Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera
ICLR 2020 From Variational to Deterministic Autoencoders Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael Black, Bernhard Schölkopf
NeurIPS 2020 Learning Kernel Tests Without Data Splitting Jonas Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
AAAI 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer
UAI 2020 On the Design of Consequential Ranking Algorithms Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez
NeurIPS 2020 Relative Gradient Optimization of the Jacobian Term in Unsupervised Deep Learning Luigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvarinen
UAI 2020 Semi-Supervised Learning, Causality, and the Conditional Cluster Assumption Julius Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf
UAI 2020 Testing Goodness of Fit of Conditional Density Models with Kernels Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
CoRL 2020 TriFinger: An Open-Source Robot for Learning Dexterity Manuel Wuthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer
ICML 2020 Weakly-Supervised Disentanglement Without Compromises Francesco Locatello, Ben Poole, Gunnar Raetsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
ICML 2019 AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer
ICML 2019 Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
UAI 2019 Coordinating Users of Shared Facilities via Data-Driven Predictive Assistants and Game Theory Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schölkopf
MLJ 2019 Data Scarcity, Robustness and Extreme Multi-Label Classification Rohit Babbar, Bernhard Schölkopf
ICLRW 2019 Disentangled State Space Models: Unsupervised Learning of Dynamics Across Heterogeneous Environments Ðorđe Miladinović, Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
ICLRW 2019 Disentangling Factors of Variations Using Few Labels Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar R¨¨ätsch, Bernhard Schölkopf, Olivier Bachem
ICML 2019 First-Order Adversarial Vulnerability of Neural Networks and Input Dimension Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou, Bernhard Schölkopf, David Lopez-Paz
ICML 2019 Kernel Mean Matching for Content Addressability of GANs Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
NeurIPS 2019 Kernel Stein Tests for Multiple Model Comparison Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum
ICLRW 2019 Learning from Samples of Variable Quality Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf
NeurIPS 2019 On the Fairness of Disentangled Representations Francesco Locatello, Gabriele Abbati, Thomas Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem
NeurIPS 2019 On the Transfer of Inductive Bias from Simulation to the Real World: A New Disentanglement Dataset Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
NeurIPS 2019 Perceiving the Arrow of Time in Autoregressive Motion Kristof Meding, Dominik Janzing, Bernhard Schölkopf, Felix A. Wichmann
JMLR 2019 Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
ICML 2019 Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter, Djordje Miladinovic, Bernhard Schölkopf, Stefan Bauer
NeurIPS 2019 Selecting Causal Brain Features with a Single Conditional Independence Test per Feature Atalanti Mastakouri, Bernhard Schölkopf, Dominik Janzing
UAI 2019 The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
NeurIPS 2018 Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models Alexander Neitz, Giambattista Parascandolo, Stefan Bauer, Bernhard Schölkopf
AISTATS 2018 Cause-Effect Inference by Comparing Regression Errors Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
ICML 2018 Detecting Non-Causal Artifacts in Multivariate Linear Regression Models Dominik Janzing, Bernhard Schölkopf
ICML 2018 Differentially Private Database Release via Kernel Mean Embeddings Matej Balog, Ilya Tolstikhin, Bernhard Schölkopf
ICLR 2018 Fidelity-Weighted Learning Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf
UAI 2018 From Deterministic ODEs to Dynamic Structural Causal Models Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
AISTATS 2018 Group Invariance Principles for Causal Generative Models Michel Besserve, Naji Shajarisales, Bernhard Schölkopf, Dominik Janzing
NeurIPS 2018 Informative Features for Model Comparison Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
JMLR 2018 Invariant Models for Causal Transfer Learning Mateo Rojas-Carulla, Bernhard Schölkopf, Richard Turner, Jonas Peters
JMLR 2018 Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions Carl-Johann Simon-Gabriel, Bernhard Schölkopf
ICML 2018 Learning Independent Causal Mechanisms Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf
ICML 2018 On Matching Pursuit and Coordinate Descent Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Raetsch, Bernhard Schölkopf, Sebastian Stich, Martin Jaggi
ECCV 2018 Spatio-Temporal Transformer Network for Video Restoration Tae Hyun Kim, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Scholkopf
ICML 2018 Tempered Adversarial Networks Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf
ECCVW 2018 The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch
NeurIPS 2017 AdaGAN: Boosting Generative Models Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf
NeurIPS 2017 Avoiding Discrimination Through Causal Reasoning Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
UAI 2017 Causal Consistency of Structural Equation Models Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
IJCAI 2017 Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf
UAI 2017 Causal Discovery from Temporally Aggregated Time Series Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao
CVPR 2017 Discovering Causal Signals in Images David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, Leon Bottou
ICCV 2017 EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis Mehdi S. M. Sajjadi, Bernhard Scholkopf, Michael Hirsch
CVPR 2017 Flexible Spatio-Temporal Networks for Video Prediction Chaochao Lu, Michael Hirsch, Bernhard Scholkopf
NeurIPS 2017 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning Shixiang Gu, Timothy Lillicrap, Richard E Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine
FnTML 2017 Kernel Mean Embedding of Distributions: A Review and Beyond Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
ICCV 2017 Learning Blind Motion Deblurring Patrick Wieschollek, Michael Hirsch, Bernhard Scholkopf, Hendrik P. A. Lensch
AISTATS 2017 Local Group Invariant Representations via Orbit Embeddings Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf
ICCV 2017 Online Video Deblurring via Dynamic Temporal Blending Network Tae Hyun Kim, Kyoung Mu Lee, Bernhard Scholkopf, Michael Hirsch
NeurIPS 2016 Consistent Kernel Mean Estimation for Functions of Random Variables Carl-Johann Simon-Gabriel, Adam Scibior, Ilya O Tolstikhin, Bernhard Schölkopf
JMLR 2016 Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, Bernhard Schölkopf
ICML 2016 Domain Adaptation with Conditional Transferable Components Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf
JMLR 2016 Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-Thresholding Algorithm Manuel Gomez-Rodriguez, Le Song, Hadi Daneshm, Bernhard Schölkopf
JMLR 2016 Kernel Mean Shrinkage Estimators Krikamol Muandet, Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
NeurIPS 2016 Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels Ilya O Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf
UAI 2016 On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour
ICML 2016 The Arrow of Time in Multivariate Time Series Stefan Bauer, Bernhard Schölkopf, Jonas Peters
ICLR 2016 Unifying Distillation and Privileged Information David Lopez-Paz, Léon Bottou, Bernhard Schölkopf, Vladimir Vapnik
IJCAI 2015 Identification of Time-Dependent Causal Model: A Gaussian Process Treatment Biwei Huang, Kun Zhang, Bernhard Schölkopf
AISTATS 2015 Inference of Cause and Effect with Unsupervised Inverse Regression Eleni Sgouritsa, Dominik Janzing, Philipp Hennig, Bernhard Schölkopf
AAAI 2015 Multi-Source Domain Adaptation: A Causal View Kun Zhang, Mingming Gong, Bernhard Schölkopf
ICML 2015 Removing Systematic Errors for Exoplanet Search via Latent Causes Bernhard Schölkopf, David Hogg, Dun Wang, Dan Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
ICCV 2015 Self-Calibration of Optical Lenses Michael Hirsch, Bernhard Scholkopf
JMLR 2015 Semi-Supervised Interpolation in an Anticausal Learning Scenario Dominik Janzing, Bernhard Schölkopf
ICML 2015 Towards a Learning Theory of Cause-Effect Inference David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, Iliya Tolstikhin
UAI 2014 A Permutation-Based Kernel Conditional Independence Test Gary Doran, Krikamol Muandet, Kun Zhang, Bernhard Schölkopf
JMLR 2014 Causal Discovery with Continuous Additive Noise Models Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
ICML 2014 Consistency of Causal Inference Under the Additive Noise Model Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schölkopf
UAI 2014 Estimating Causal Effects by Bounding Confounding Philipp Geiger, Dominik Janzing, Bernhard Schölkopf
UAI 2014 Inferring Latent Structures via Information Inequalities Rafael Chaves, Lukas Luft, Thiago O. Maciel, David Gross, Dominik Janzing, Bernhard Schölkopf
NeurIPS 2014 Kernel Mean Estimation via Spectral Filtering Krikamol Muandet, Bharath Sriperumbudur, Bernhard Schölkopf
COLT 2014 Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf
CVPR 2014 Seeing the Arrow of Time Lyndsey C. Pickup, Zheng Pan, Donglai Wei, YiChang Shih, Changshui Zhang, Andrew Zisserman, Bernhard Scholkopf, William T. Freeman
AISTATS 2014 Towards Building a Crowd-Sourced Sky mAP Dustin Lang, David W. Hogg, Bernhard Schölkopf
CVPR 2013 A Machine Learning Approach for Non-Blind Image Deconvolution Christian J. Schuler, Harold Christopher Burger, Stefan Harmeling, Bernhard Scholkopf
NeurIPS 2013 Causal Inference on Time Series Using Restricted Structural Equation Models Jonas Peters, Dominik Janzing, Bernhard Schölkopf
ICML 2013 Domain Adaptation Under Target and Conditional Shift Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang
ICML 2013 Domain Generalization via Invariant Feature Representation Krikamol Muandet, David Balduzzi, Bernhard Schölkopf
UAI 2013 From Ordinary Differential Equations to Structural Causal Models: The Deterministic Case Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
UAI 2013 Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
ICML 2013 Modeling Information Propagation with Survival Theory Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
CVPR 2013 On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit Stefan Harmeling, Michael Hirsch, Bernhard Scholkopf
UAI 2013 One-Class Support Measure Machines for Group Anomaly Detection Krikamol Muandet, Bernhard Schölkopf
NeurIPS 2013 Statistical Analysis of Coupled Time Series with Kernel Cross-Spectral Density Operators. Michel Besserve, Nikos K. Logothetis, Bernhard Schölkopf
NeurIPS 2013 The Randomized Dependence Coefficient David Lopez-Paz, Philipp Hennig, Bernhard Schölkopf
JMLR 2012 A Kernel Two-Sample Test Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander Smola
ECCV 2012 Blind Correction of Optical Aberrations Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
ICML 2012 Influence Maximization in Continuous Time Diffusion Networks Manuel Gomez-Rodriguez, Bernhard Schölkopf
NeurIPS 2012 Learning from Distributions via Support Measure Machines Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf
ICML 2012 On Causal and Anticausal Learning Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij
ECCV 2012 Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database Rolf Köhler, Michael Hirsch, Betty J. Mohler, Bernhard Schölkopf, Stefan Harmeling
NeurIPS 2012 Semi-Supervised Domain Adaptation with Non-Parametric Copulas David Lopez-paz, Jose M. Hernández-lobato, Bernhard Schölkopf
ICML 2012 Submodular Inference of Diffusion Networks from Multiple Trees Manuel Gomez-Rodriguez, Bernhard Schölkopf
NeurIPS 2012 The Representer Theorem for Hilbert Spaces: A Necessary and Sufficient Condition Francesco Dinuzzo, Bernhard Schölkopf
UAI 2011 Detecting Low-Complexity Unobserved Causes Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf
ICCV 2011 Fast Removal of Non-Uniform Camera Shake Michael Hirsch, Christian J. Schuler, Stefan Harmeling, Bernhard Schölkopf
UAI 2011 Identifiability of Causal Graphs Using Functional Models Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
UAI 2011 Kernel-Based Conditional Independence Test and Application in Causal Discovery Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf
MLJ 2011 Multi-Way Set Enumeration in Weight Tensors Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf
ICCV 2011 Non-Stationary Correction of Optical Aberrations Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
NeurIPS 2011 On Causal Discovery with Cyclic Additive Noise Models Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf
NeurIPS 2011 Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf, Peter V. Gehler
ICML 2011 Support Vector Machines as Probabilistic Models Vojtech Franc, Alexander Zien, Bernhard Schölkopf
ICML 2011 Uncovering the Temporal Dynamics of Diffusion Networks Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schölkopf
COLT 2010 Causal Markov Condition for Submodular Information Measures Bastian Steudel, Dominik Janzing, Bernhard Schölkopf
CVPR 2010 Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution Michael Hirsch, Suvrit Sra, Bernhard Schölkopf, Stefan Harmeling
JMLR 2010 Hilbert Space Embeddings and Metrics on Probability Measures Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R.G. Lanckriet
AISTATS 2010 Identifying Cause and Effect on Discrete Data Using Additive Noise Models Jonas Peters, Dominik Janzing, Bernhard Schölkopf
UAI 2010 Inferring Deterministic Causal Relations Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf
UAI 2010 Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery Kun Zhang, Bernhard Schölkopf, Dominik Janzing
NeurIPS 2010 Probabilistic Latent Variable Models for Distinguishing Between Cause and Effect Oliver Stegle, Dominik Janzing, Kun Zhang, Joris M. Mooij, Bernhard Schölkopf
NeurIPS 2010 Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake Stefan Harmeling, Hirsch Michael, Bernhard Schölkopf
NeurIPS 2010 Switched Latent Force Models for Movement Segmentation Mauricio Alvarez, Jan R. Peters, Neil D. Lawrence, Bernhard Schölkopf
ICML 2010 Telling Cause from Effect Based on High-Dimensional Observations Dominik Janzing, Patrik O. Hoyer, Bernhard Schölkopf
ICML 2009 Detecting the Direction of Causal Time Series Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf
UAI 2009 Identifying Confounders Using Additive Noise Models Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf
NeurIPS 2009 Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions Kenji Fukumizu, Arthur Gretton, Gert R. Lanckriet, Bernhard Schölkopf, Bharath K. Sriperumbudur
CVPR 2009 Learning Similarity Measure for Multi-Modal 3D Image Registration Daewon Lee, Matthias Hofmann, Florian Steinke, Yasemin Altun, Nathan D. Cahill, Bernhard Schölkopf
ICML 2009 Regression by Dependence Minimization and Its Application to Causal Inference in Additive Noise Models Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
NeurIPS 2008 An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis Gabriele Schweikert, Gunnar Rätsch, Christian K. Widmer, Bernhard Schölkopf
ECCV 2008 Automatic Image Colorization via Multimodal Predictions Guillaume Charpiat, Matthias Hofmann, Bernhard Schölkopf
NeurIPS 2008 Bayesian Experimental Design of Magnetic Resonance Imaging Sequences Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf, Matthias Seeger
NeurIPS 2008 Characteristic Kernels on Groups and Semigroups Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur
NeurIPS 2008 Diffeomorphic Dimensionality Reduction Christian Walder, Bernhard Schölkopf
NeurIPS 2008 Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Biessmann, Bernhard Schölkopf
COLT 2008 Injective Hilbert Space Embeddings of Probability Measures Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
NeurIPS 2008 Nonlinear Causal Discovery with Additive Noise Models Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf
ICML 2008 Sparse Multiscale Gaussian Process Regression Christian Walder, Kwang In Kim, Bernhard Schölkopf
ICML 2008 Tailoring Density Estimation via Reproducing Kernel Moment Matching Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schölkopf
ALT 2007 A Hilbert Space Embedding for Distributions Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
AAAI 2007 A Kernel Approach to Comparing Distributions Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
NeurIPS 2007 A Kernel Statistical Test of Independence Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf, Alex J. Smola
ICML 2007 A Kernel-Based Causal Learning Algorithm Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu
NeurIPS 2007 An Analysis of Inference with the Universum Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz, Bernhard Schölkopf
NeurIPS 2007 Kernel Measures of Conditional Dependence Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf
ICML 2007 Local Learning Projections Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf
JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson
AISTATS 2007 Transductive Classification via Local Learning Regularization Mingrui Wu, Bernhard Schölkopf
JMLR 2006 A Direct Method for Building Sparse Kernel Learning Algorithms Mingrui Wu, Bernhard Schölkopf, Gökhan Bakir
NeurIPS 2006 A Kernel Method for the Two-Sample-Problem Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alex J. Smola
NeurIPS 2006 A Local Learning Approach for Clustering Mingrui Wu, Bernhard Schölkopf
NeurIPS 2006 A Nonparametric Approach to Bottom-up Visual Saliency Wolf Kienzle, Felix A. Wichmann, Matthias O. Franz, Bernhard Schölkopf
NeurIPS 2006 Correcting Sample Selection Bias by Unlabeled Data Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, Alex J. Smola
NeurIPS 2006 Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions Christian Walder, Olivier Chapelle, Bernhard Schölkopf
JMLR 2006 Large Scale Multiple Kernel Learning Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf
NeurIPS 2006 Learning Dense 3D Correspondence Florian Steinke, Volker Blanz, Bernhard Schölkopf
CVPRW 2006 Learning an Interest Operator from Human Eye Movements Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz
NeurIPS 2006 Learning with Hypergraphs: Clustering, Classification, and Embedding Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
ICML 2005 A Brain Computer Interface with Online Feedback Based on Magnetoencephalography Thomas Navin Lal, Michael Schröder, N. Jeremy Hill, Hubert Preißl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schölkopf
ICML 2005 Building Sparse Large Margin Classifiers Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
ICML 2005 Implicit Surface Modelling as an Eigenvalue Problem Christian Walder, Olivier Chapelle, Bernhard Schölkopf
AISTATS 2005 Kernel Constrained Covariance for Dependence Measurement Arthur Gretton, Alexander Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos Logothetis
JMLR 2005 Kernel Methods for Measuring Independence Arthur Gretton, Ralf Herbrich, Alexander Smola, Olivier Bousquet, Bernhard Schölkopf
ICML 2005 Large Scale Genomic Sequence SVM Classifiers Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf
ICML 2005 Learning from Labeled and Unlabeled Data on a Directed Graph Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
ALT 2005 Measuring Statistical Dependence with Hilbert-Schmidt Norms Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf
ICML 2005 Object Correspondence as a Machine Learning Problem Bernhard Schölkopf, Florian Steinke, Volker Blanz
ECML-PKDD 2005 Training Support Vector Machines with Multiple Equality Constraints Wolf Kienzle, Bernhard Schölkopf
JMLR 2004 A Compression Approach to Support Vector Model Selection Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf
ICML 2004 A Kernel View of the Dimensionality Reduction of Manifolds Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf
NeurIPS 2004 An Auditory Paradigm for Brain-Computer Interfaces N. J. Hill, Thomas N. Lal, Karin Bierig, Niels Birbaumer, Bernhard Schölkopf
NeurIPS 2004 Face Detection --- Efficient and Rank Deficient Wolf Kienzle, Matthias O. Franz, Bernhard Schölkopf, Gökhan H. Bakir
NeurIPS 2004 Implicit Wiener Series for Higher-Order Image Analysis Matthias O. Franz, Bernhard Schölkopf
NeurIPS 2004 Kernel Methods for Implicit Surface Modeling Joachim Giesen, Simon Spalinger, Bernhard Schölkopf
NeurIPS 2004 Machine Learning Applied to Perception: Decision Images for Gender Classification Felix A. Wichmann, Arnulf B. Graf, Heinrich H. Bülthoff, Eero P. Simoncelli, Bernhard Schölkopf
NeurIPS 2004 Methods Towards Invasive Human Brain Computer Interfaces Thomas N. Lal, Thilo Hinterberger, Guido Widman, Michael Schröder, N. J. Hill, Wolfgang Rosenstiel, Christian E. Elger, Niels Birbaumer, Bernhard Schölkopf
NeurIPS 2004 Semi-Supervised Learning on Directed Graphs Dengyong Zhou, Thomas Hofmann, Bernhard Schölkopf
COLT 2003 Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings Bernhard Schölkopf, Manfred K. Warmuth
NeurIPS 2003 Learning to Find Pre-Images Jason Weston, Bernhard Schölkopf, Gökhan H. Bakir
NeurIPS 2003 Learning with Local and Global Consistency Dengyong Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf
NeurIPS 2003 Prediction on Spike Data Using Kernel Algorithms Jan Eichhorn, Andreas Tolias, Alexander Zien, Malte Kuss, Jason Weston, Nikos Logothetis, Bernhard Schölkopf, Carl E. Rasmussen
NeurIPS 2003 Ranking on Data Manifolds Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
ECML-PKDD 2002 A Kernel Approach for Learning from Almost Orthogonal Patterns Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
NeurIPS 2002 Cluster Kernels for Semi-Supervised Learning Olivier Chapelle, Jason Weston, Bernhard Schölkopf
NeurIPS 2002 Kernel Dependency Estimation Jason Weston, Olivier Chapelle, Vladimir Vapnik, André Elisseeff, Bernhard Schölkopf
MLJ 2002 Training Invariant Support Vector Machines Dennis DeCoste, Bernhard Schölkopf
COLT 2001 A Generalized Representer Theorem Bernhard Schölkopf, Ralf Herbrich, Alexander J. Smola
AISTATS 2001 A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds Michael E. Tipping, Bernhard Schölkopf
AISTATS 2001 An Improved Training Algorithm for Kernel Fisher Discriminants Sebastian Mika, Alexander J. Smola, Bernhard Schölkopf
ICCV 2001 Computationally Efficient Face Detection Sami Romdhani, Philip H. S. Torr, Bernhard Schölkopf, Andrew Blake
ICML 2001 Estimating a Kernel Fisher Discriminant in the Presence of Label Noise Neil D. Lawrence, Bernhard Schölkopf
NeCo 2001 Estimating the Support of a High-Dimensional Distribution Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alexander J. Smola, Robert C. Williamson
NeurIPS 2001 Incorporating Invariances in Non-Linear Support Vector Machines Olivier Chapelle, Bernhard Schölkopf
ICCV 2001 Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation Stan Z. Li, QingDong Fu, Lie Gu, Bernhard Schölkopf, Yimin Cheng, HongJiang Zhang
JMLR 2001 Regularized Principal Manifolds (Kernel Machines Section) Alexander J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
NeurIPS 2001 Sampling Techniques for Kernel Methods Dimitris Achlioptas, Frank Mcsherry, Bernhard Schölkopf
COLT 2000 Entropy Numbers of Linear Function Classes Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
NeurIPS 2000 Four-Legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas
NeCo 2000 New Support Vector Algorithms Bernhard Schölkopf, Alexander J. Smola, Robert C. Williamson, Peter L. Bartlett
ICML 2000 Sparse Greedy Matrix Approximation for Machine Learning Alexander J. Smola, Bernhard Schölkopf
NeurIPS 2000 Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
NeurIPS 2000 The Kernel Trick for Distances Bernhard Schölkopf
NeurIPS 1999 Invariant Feature Extraction and Classification in Kernel Spaces Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
NeurIPS 1999 Support Vector Method for Novelty Detection Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
NeurIPS 1999 The Entropy Regularization Information Criterion Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
NeurIPS 1999 V-Arc: Ensemble Learning in the Presence of Outliers Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
NeurIPS 1998 Kernel PCA and De-Noising in Feature Spaces Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
NeCo 1998 Nonlinear Component Analysis as a Kernel Eigenvalue Problem Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
NeurIPS 1998 Semiparametric Support Vector and Linear Programming Machines Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
NeurIPS 1998 Shrinking the Tube: A New Support Vector Regression Algorithm Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson
NeurIPS 1997 From Regularization Operators to Support Vector Kernels Alex J. Smola, Bernhard Schölkopf
NeurIPS 1997 Prior Knowledge in Support Vector Kernels Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik
NeurIPS 1996 Improving the Accuracy and Speed of Support Vector Machines Christopher J. C. Burges, Bernhard Schölkopf