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ORCIDBernhard Schölkopf
Person information
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
- award (2018): Gottfried Wilhelm Leibniz Prize
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2020 – today
- 2022
[j105]Lukas Kondmann
, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiao Xiang Zhu:
Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022)- [c340]Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet:
A Witness Two-Sample Test. AISTATS 2022: 1403-1419 - [c339]Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf:
A prior-based approximate latent Riemannian metric. AISTATS 2022: 4634-4658 - [c338]Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato:
Resampling Base Distributions of Normalizing Flows. AISTATS 2022: 4915-4936 - [c337]Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schölkopf:
Adversarially Robust Kernel Smoothing. AISTATS 2022: 4972-4994 - [c336]Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf:
GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL. AISTATS 2022: 7518-7530 - [i237]Arash Mehrjou, Ashkan Soleymani, Stefan Bauer, Bernhard Schölkopf:
Physical Derivatives: Computing policy gradients by physical forward-propagation. CoRR abs/2201.05830 (2022) - [i236]Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello:
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. CoRR abs/2201.13388 (2022) - [i235]Luigi Gresele, Julius von Kügelgen, Jonas M. Kübler, Elke Kirschbaum, Bernhard Schölkopf, Dominik Janzing:
Causal Inference Through the Structural Causal Marginal Problem. CoRR abs/2202.01300 (2022) - [i234]Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf:
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective". CoRR abs/2202.06844 (2022) - [i233]Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf:
Logical Fallacy Detection. CoRR abs/2202.13758 (2022) - [i232]Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer:
Interventions, Where and How? Experimental Design for Causal Models at Scale. CoRR abs/2203.02016 (2022) - [i231]Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello:
Score matching enables causal discovery of nonlinear additive noise models. CoRR abs/2203.04413 (2022) - [i230]Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell:
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CoRR abs/2203.04913 (2022) - [i229]Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf:
Phenomenology of Double Descent in Finite-Width Neural Networks. CoRR abs/2203.07337 (2022) - [i228]Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár:
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. CoRR abs/2203.15756 (2022) - [i227]Bernhard Schölkopf, Julius von Kügelgen:
From Statistical to Causal Learning. CoRR abs/2204.00607 (2022) - [i226]Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf:
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework. CoRR abs/2204.03439 (2022) - [i225]Yassine Nemmour, Heiner Kremer, Bernhard Schölkopf, Jia-Jie Zhu:
Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee. CoRR abs/2204.11564 (2022) - [i224]Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf:
Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. CoRR abs/2205.02293 (2022) - [i223]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. CoRR abs/2205.12934 (2022) - [i222]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. CoRR abs/2206.01665 (2022) - [i221]Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf:
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis. CoRR abs/2206.02013 (2022) - [i220]Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve:
Embrace the Gap: VAEs Perform Independent Mechanism Analysis. CoRR abs/2206.02416 (2022) - [i219]Aniket Das, Bernhard Schölkopf, Michael Muehlebach:
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. CoRR abs/2206.02953 (2022) - [i218]Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf:
AutoML Two-Sample Test. CoRR abs/2206.08843 (2022) - [i217]Anson Lei, Bernhard Schölkopf, Ingmar Posner:
Variational Causal Dynamics: Discovering Modular World Models from Interventions. CoRR abs/2206.11131 (2022) - 2021
- [j104]Tobias Hepp, Dominik Blum, Karim Armanious, Bernhard Schölkopf, Darko Stern, Bin Yang, Sergios Gatidis:
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. 92: 101967 (2021) - [j103]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Toward Causal Representation Learning. Proc. IEEE 109(5): 612-634 (2021) - [j102]Julius von Kügelgen, Luigi Gresele, Bernhard Schölkopf:
Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects. IEEE Trans. Artif. Intell. 2(1): 18-27 (2021) - [j101]Samuel Bustamante, Jan Peters, Bernhard Schölkopf, Moritz Grosse-Wentrup, Vinay Jayaram:
ArmSym: A Virtual Human-Robot Interaction Laboratory for Assistive Robotics. IEEE Trans. Hum. Mach. Syst. 51(6): 568-577 (2021) - [c335]Michel Besserve, Rémy Sun, Dominik Janzing, Bernhard Schölkopf:
A Theory of Independent Mechanisms for Extrapolation in Generative Models. AAAI 2021: 6741-6749 - [c334]Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf:
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. AISTATS 2021: 280-288 - [c333]Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf:
Geometrically Enriched Latent Spaces. AISTATS 2021: 631-639 - [c332]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. AISTATS 2021: 1180-1188 - [c331]Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schölkopf, Rada Mihalcea:
Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States. EMNLP (Findings) 2021: 288-301 - [c330]Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf:
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. EMNLP (1) 2021: 9499-9513 - [c329]Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera:
Algorithmic Recourse: from Counterfactual Explanations to Interventions. FAccT 2021: 353-362 - [c328]Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer:
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR 2021 - [c327]Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams:
Predicting Infectiousness for Proactive Contact Tracing. ICLR 2021 - [c326]Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf:
On the Transfer of Disentangled Representations in Realistic Settings. ICLR 2021 - [c325]Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf:
Recurrent Independent Mechanisms. ICLR 2021 - [c324]Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio:
Fast And Slow Learning Of Recurrent Independent Mechanisms. ICLR 2021 - [c323]Alexander Neitz, Giambattista Parascandolo, Bernhard Schölkopf:
A teacher-student framework to distill future trajectories. ICLR 2021 - [c322]Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf:
Learning explanations that are hard to vary. ICLR 2021 - [c321]Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf:
Spatially Structured Recurrent Modules. ICLR 2021 - [c320]Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis:
Bayesian Quadrature on Riemannian Data Manifolds. ICML 2021: 3459-3468 - [c319]Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf:
Function Contrastive Learning of Transferable Meta-Representations. ICML 2021: 3755-3765 - [c318]Atalanti-Anastasia Mastakouri, Bernhard Schölkopf, Dominik Janzing:
Necessary and sufficient conditions for causal feature selection in time series with latent common causes. ICML 2021: 7502-7511 - [c317]Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet:
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression. ICML 2021: 8401-8412 - [c316]Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf:
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning. ICML 2021: 9848-9858 - [c315]Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer:
On Disentangled Representations Learned from Correlated Data. ICML 2021: 10401-10412 - [c314]Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf:
Neural Lyapunov Redesign. L4DC 2021: 459-470 - [c313]Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu:
Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach. L4DC 2021: 1255-1269 - [c312]Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler:
Backward-Compatible Prediction Updates: A Probabilistic Approach. NeurIPS 2021: 116-128 - [c311]Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause:
Regret Bounds for Gaussian-Process Optimization in Large Domains. NeurIPS 2021: 7385-7396 - [c310]Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf:
Dynamic Inference with Neural Interpreters. NeurIPS 2021: 10985-10998 - [c309]Jonas M. Kübler, Simon Buchholz, Bernhard Schölkopf:
The Inductive Bias of Quantum Kernels. NeurIPS 2021: 12661-12673 - [c308]Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello:
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. NeurIPS 2021: 16451-16467 - [c307]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. NeurIPS 2021: 21681-21695 - [c306]Maximilian Seitzer, Bernhard Schölkopf, Georg Martius:
Causal Influence Detection for Improving Efficiency in Reinforcement Learning. NeurIPS 2021: 22905-22918 - [c305]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. NeurIPS 2021: 24111-24123 - [c304]Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve:
Independent mechanism analysis, a new concept? NeurIPS 2021: 28233-28248 - [i216]Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet:
An Optimal Witness Function for Two-Sample Testing. CoRR abs/2102.05573 (2021) - [i215]Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis:
Bayesian Quadrature on Riemannian Data Manifolds. CoRR abs/2102.06645 (2021) - [i214]Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet:
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression. CoRR abs/2102.08208 (2021) - [i213]Jia-Jie Zhu, Yassine Nemmour, Bernhard Schölkopf:
From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing. CoRR abs/2102.08474 (2021) - [i212]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Towards Causal Representation Learning. CoRR abs/2102.11107 (2021) - [i211]Maximilian Mordig, Riccardo Della Vecchia, Nicolò Cesa-Bianchi, Bernhard Schölkopf:
Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners. CoRR abs/2102.11834 (2021) - [i210]Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf:
Nonlinear Invariant Risk Minimization: A Causal Approach. CoRR abs/2102.12353 (2021) - [i209]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. CoRR abs/2103.01649 (2021) - [i208]Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf:
A prior-based approximate latent Riemannian metric. CoRR abs/2103.05290 (2021) - [i207]Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Bernhard Schölkopf, Stefan Bauer:
Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases. CoRR abs/2103.15561 (2021) - [i206]Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause:
Regret Bounds for Gaussian-Process Optimization in Large Domains. CoRR abs/2104.14113 (2021) - [i205]Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio:
Fast and Slow Learning of Recurrent Independent Mechanisms. CoRR abs/2105.08710 (2021) - [i204]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. CoRR abs/2105.11839 (2021) - [i203]Rui Zhang, Krikamol Muandet, Bernhard Schölkopf, Masaaki Imaizumi:
Instrument Space Selection for Kernel Maximum Moment Restriction. CoRR abs/2106.03340 (2021) - [i202]Maximilian Seitzer, Bernhard Schölkopf, Georg Martius:
Causal Influence Detection for Improving Efficiency in Reinforcement Learning. CoRR abs/2106.03443 (2021) - [i201]Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello:
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. CoRR abs/2106.04619 (2021) - [i200]Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve:
Independent mechanism analysis, a new concept? CoRR abs/2106.05200 (2021) - [i199]Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang:
Adversarial Robustness through the Lens of Causality. CoRR abs/2106.06196 (2021) - [i198]Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler:
Towards Total Recall in Industrial Anomaly Detection. CoRR abs/2106.08265 (2021) - [i197]Julius von Kügelgen, Nikita Agarwal, Jakob Zeitler, Afsaneh Mastouri, Bernhard Schölkopf:
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects. CoRR abs/2106.11849 (2021) - [i196]Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Real-time gravitational-wave science with neural posterior estimation. CoRR abs/2106.12594 (2021) - [i195]Diego Agudelo-España, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu:
Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics. CoRR abs/2106.13066 (2021) - [i194]Felix Leeb, Stefan Bauer, Bernhard Schölkopf:
Interventional Assays for the Latent Space of Autoencoders. CoRR abs/2106.16091 (2021) - [i193]Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello:
Generalization and Robustness Implications in Object-Centric Learning. CoRR abs/2107.00637 (2021) - [i192]Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler:
Backward-Compatible Prediction Updates: A Probabilistic Approach. CoRR abs/2107.01057 (2021) - [i191]Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf:
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. CoRR abs/2107.05446 (2021) - [i190]Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR abs/2107.05686 (2021) - [i189]Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter V. Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel:
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. CoRR abs/2107.08221 (2021) - [i188]Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke:
Learning Neural Causal Models with Active Interventions. CoRR abs/2109.02429 (2021) - [i187]Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf:
Direct Advantage Estimation. CoRR abs/2109.06093 (2021) - [i186]Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles B. Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf:
A Robot Cluster for Reproducible Research in Dexterous Manipulation. CoRR abs/2109.10957 (2021) - [i185]Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiaoxiang Zhu:
Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. CoRR abs/2110.02068 (2021) - [i184]Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf:
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. CoRR abs/2110.03618 (2021) - [i183]Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf:
Boxhead: A Dataset for Learning Hierarchical Representations. CoRR abs/2110.03628 (2021) - [i182]Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf:
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. CoRR abs/2110.05304 (2021) - [i181]Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang:
Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR abs/2110.05721 (2021) - [i180]Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf:
Dynamic Inference with Neural Interpreters. CoRR abs/2110.06399 (2021) - [i179]Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf:
Unsupervised Object Learning via Common Fate. CoRR abs/2110.06562 (2021) - [i178]Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu:
Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control. CoRR abs/2110.13588 (2021) - [i177]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. CoRR abs/2110.14432 (2021) - [i176]Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf:
GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL. CoRR abs/2110.15489 (2021) - [i175]Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato:
Resampling Base Distributions of Normalizing Flows. CoRR abs/2110.15828 (2021) - [i174]Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke:
Group equivariant neural posterior estimation. CoRR abs/2111.13139 (2021) - [i173]Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CoRR abs/2111.13839 (2021) - [i172]Michel Besserve, Bernhard Schölkopf:
Learning soft interventions in complex equilibrium systems. CoRR abs/2112.05729 (2021) - [i171]Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Bernhard Schölkopf:
On the Adversarial Robustness of Causal Algorithmic Recourse. CoRR abs/2112.11313 (2021) - 2020
- [j100]Olga Mineeva, Mateo Rojas-Carulla, Ruth Ley, Bernhard Schölkopf, Nicholas Youngblut:
DeepMAsED: evaluating the quality of metagenomic assemblies. Bioinform. 36(10): 3011-3017 (2020) - [j99]Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf:
Causal Discovery from Heterogeneous/Nonstationary Data. J. Mach. Learn. Res. 21: 89:1-89:53 (2020) - [j98]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. J. Mach. Learn. Res. 21: 209:1-209:62 (2020) - [j97]Sebastián Gómez-González, Sergey Prokudin, Bernhard Schölkopf, Jan Peters:
Real Time Trajectory Prediction Using Deep Conditional Generative Models. IEEE Robotics Autom. Lett. 5(2): 970-976 (2020) - [j96]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Adaptation and Robust Learning of Probabilistic Movement Primitives. IEEE Trans. Robotics 36(2): 366-379 (2020) - [c303]Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020: 6364-6371 - [c302]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Commentary on the Unsupervised Learning of Disentangled Representations. AAAI 2020: 13681-13684 - [c301]Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera:
Fair Decisions Despite Imperfect Predictions. AISTATS 2020: 277-287 - [c300]Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf:
Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. CDC 2020: 3457-3463 - [c299]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:
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