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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
- 2024
[j122]Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach:
Deep Backtracking Counterfactuals for Causally Compliant Explanations. Trans. Mach. Learn. Res. 2024 (2024)- [j121]Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf:
Towards fully covariant machine learning. Trans. Mach. Learn. Res. 2024 (2024) - [c451]Flavio Schneider, Ojasv Kamal, Zhijing Jin, Bernhard Schölkopf:
Moûsai: Efficient Text-to-Music Diffusion Models. ACL (1) 2024: 8050-8068 - [c450]Ishan Agrawal, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Mrinmaya Sachan, Bernhard Schölkopf:
CausalCite: A Causal Formulation of Paper Citations. ACL (Findings) 2024: 8395-8410 - [c449]Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf:
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. ACL (1) 2024: 8420-8436 - [c448]Lars Lorch, Andreas Krause, Bernhard Schölkopf:
Causal Modeling with Stationary Diffusions. AISTATS 2024: 1927-1935 - [c447]Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf:
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs. CVPR 2024: 21295-21304 - [c446]Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez Adauto, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan:
Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis. EMNLP (Findings) 2024: 9353-9372 - [c445]Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan:
Implicit Personalization in Language Models: A Systematic Study. EMNLP (Findings) 2024: 12309-12325 - [c444]Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings:
The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. EMNLP 2024: 16722-16763 - [c443]Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf:
Out-of-Variable Generalisation for Discriminative Models. ICLR 2024 - [c442]Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf:
Can Large Language Models Infer Causation from Correlation? ICLR 2024 - [c441]Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf:
Ghost on the Shell: An Expressive Representation of General 3D Shapes. ICLR 2024 - [c440]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:
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. ICLR 2024 - [c439]Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz:
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. ICLR 2024 - [c438]Hsiao-Ru Pan, Bernhard Schölkopf:
Skill or Luck? Return Decomposition via Advantage Functions. ICLR 2024 - [c437]Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Haeufle, Bernhard Schölkopf, Dieter Büchler:
Identifying Policy Gradient Subspaces. ICLR 2024 - [c436]Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina:
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. ICLR 2024 - [c435]Simon Buchholz, Bernhard Schölkopf:
Robustness of Nonlinear Representation Learning. ICML 2024 - [c434]Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf:
Provable Privacy with Non-Private Pre-Processing. ICML 2024 - [c433]Heiner Kremer, Bernhard Schölkopf:
Geometry-Aware Instrumental Variable Regression. ICML 2024 - [c432]Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan:
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? ICML 2024 - [c431]Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang:
Detecting and Identifying Selection Structure in Sequential Data. ICML 2024 - [c430]Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c429]Felix Leeb, Bernhard Schölkopf:
A diverse Multilingual News Headlines Dataset from around the World. NAACL (Short Papers) 2024: 647-652 - [c428]Zhijing Jin, Yuen Chen, Fernando Gonzalez Adauto, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab:
Analyzing the Role of Semantic Representations in the Era of Large Language Models. NAACL-HLT 2024: 3781-3798 - [c427]Jonathan Thomm
, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzic, Bernhard Schölkopf, Abbas Rahimi:
Terminating Differentiable Tree Experts. NeSy (1) 2024: 296-311 - [i359]Partha Ghosh, Soubhik Sanyal, Cordelia Schmid, Bernhard Schölkopf:
RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks. CoRR abs/2401.06035 (2024) - [i358]Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Häufle, Bernhard Schölkopf, Dieter Büchler:
Identifying Policy Gradient Subspaces. CoRR abs/2401.06604 (2024) - [i357]Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan:
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? CoRR abs/2401.18070 (2024) - [i356]Alice Bizeul, Bernhard Schölkopf, Carl Allen:
A Probabilistic Model to explain Self-Supervised Representation Learning. CoRR abs/2402.01399 (2024) - [i355]Alexander Song, Sai Nikhilesh Murty Kottapalli, Rahul Goyal, Bernhard Schölkopf, Peer Fischer:
Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light. CoRR abs/2402.01988 (2024) - [i354]Jonathan Thomm, Aleksandar Terzic, Geethan Karunaratne, Giacomo Camposampiero, Bernhard Schölkopf, Abbas Rahimi:
Limits of Transformer Language Models on Learning Algorithmic Compositions. CoRR abs/2402.05785 (2024) - [i353]Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang:
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR abs/2402.06665 (2024) - [i352]Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. CoRR abs/2402.09236 (2024) - [i351]Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf:
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. CoRR abs/2402.11655 (2024) - [i350]Hsiao-Ru Pan, Bernhard Schölkopf:
Skill or Luck? Return Decomposition via Advantage Functions. CoRR abs/2402.12874 (2024) - [i349]Adithya Kumar Chinnakkonda Ravi, Victor Dhédin, Armand Jordana, Huaijiang Zhu, Avadesh Meduri, Ludovic Righetti, Bernhard Schölkopf, Majid Khadiv:
Efficient Search and Learning for Agile Locomotion on Stepping Stones. CoRR abs/2403.03639 (2024) - [i348]Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf:
Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. CoRR abs/2403.07379 (2024) - [i347]Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf:
Provable Privacy with Non-Private Pre-Processing. CoRR abs/2403.13041 (2024) - [i346]Nasim Rahaman, Martin Weiss, Manuel Wüthrich, Yoshua Bengio, Li Erran Li, Chris Pal, Bernhard Schölkopf:
Language Models Can Reduce Asymmetry in Information Markets. CoRR abs/2403.14443 (2024) - [i345]Felix Leeb, Bernhard Schölkopf:
A diverse Multilingual News Headlines Dataset from around the World. CoRR abs/2403.19352 (2024) - [i344]Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan:
On the Causal Nature of Sentiment Analysis. CoRR abs/2404.11055 (2024) - [i343]Anson Lei, Frederik Nolte, Bernhard Schölkopf, Ingmar Posner:
Compete and Compose: Learning Independent Mechanisms for Modular World Models. CoRR abs/2404.15109 (2024) - [i342]Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea:
Cooperate or Collapse: Emergence of Sustainability Behaviors in a Society of LLM Agents. CoRR abs/2404.16698 (2024) - [i341]Zhijing Jin, Yuen Chen, Fernando Gonzalez, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab:
Analyzing the Role of Semantic Representations in the Era of Large Language Models. CoRR abs/2405.01502 (2024) - [i340]Heiner Kremer, Bernhard Schölkopf:
Geometry-Aware Instrumental Variable Regression. CoRR abs/2405.11633 (2024) - [i339]Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan:
Implicit Personalization in Language Models: A Systematic Study. CoRR abs/2405.14808 (2024) - [i338]Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf:
Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR abs/2405.15485 (2024) - [i337]Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf:
Do Finetti: On Causal Effects for Exchangeable Data. CoRR abs/2405.18836 (2024) - [i336]Roberto Ceraolo, Dmitrii Kharlapenko, Amélie Reymond, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin:
CausalQuest: Collecting Natural Causal Questions for AI Agents. CoRR abs/2405.20318 (2024) - [i335]Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell:
On Affine Homotopy between Language Encoders. CoRR abs/2406.02329 (2024) - [i334]Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu:
Verbalized Machine Learning: Revisiting Machine Learning with Language Models. CoRR abs/2406.04344 (2024) - [i333]Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause:
Standardizing Structural Causal Models. CoRR abs/2406.11601 (2024) - [i332]Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel:
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. CoRR abs/2406.14302 (2024) - [i331]Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann:
Landscaping Linear Mode Connectivity. CoRR abs/2406.16300 (2024) - [i330]Alizée Pace, Bernhard Schölkopf, Gunnar Rätsch, Giorgia Ramponi:
Preference Elicitation for Offline Reinforcement Learning. CoRR abs/2406.18450 (2024) - [i329]Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf:
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation. CoRR abs/2406.19049 (2024) - [i328]Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings:
The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. CoRR abs/2406.19307 (2024) - [i327]Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang:
Detecting and Identifying Selection Structure in Sequential Data. CoRR abs/2407.00529 (2024) - [i326]Jonathan Thomm, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzic, Bernhard Schölkopf, Abbas Rahimi:
Terminating Differentiable Tree Experts. CoRR abs/2407.02060 (2024) - [i325]Zhijing Jin, Sydney Levine, Max Kleiman-Weiner, Giorgio Piatti, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf:
Multilingual Trolley Problems for Language Models. CoRR abs/2407.02273 (2024) - [i324]Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf:
Real-time gravitational-wave inference for binary neutron stars using machine learning. CoRR abs/2407.09602 (2024) - [i323]Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Can Large Language Models Understand Symbolic Graphics Programs? CoRR abs/2408.08313 (2024) - [i322]Yi Zhao, Le Chen, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler:
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands. CoRR abs/2408.11048 (2024) - [i321]Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach:
Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. CoRR abs/2410.01660 (2024) - [i320]Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan:
MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. CoRR abs/2410.13502 (2024) - [i319]Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Annalena Kofler, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf:
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels. CoRR abs/2410.21477 (2024) - 2023
- [j120]Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
Reinforcement learning with model-based feedforward inputs for robotic table tennis. Auton. Robots 47(8): 1387-1403 (2023) - [j119]Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, Isabel Valera:
A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations. ACM Comput. Surv. 55(5): 95:1-95:29 (2023) - [j118]Felix Laumann, Julius von Kügelgen, Junhyung Park, Bernhard Schölkopf, Mauricio Barahona:
Kernel-Based Independence Tests for Causal Structure Learning on Functional Data. Entropy 25(12): 1597 (2023) - [j117]Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey:
Metrizing Weak Convergence with Maximum Mean Discrepancies. J. Mach. Learn. Res. 24: 184:1-184:20 (2023) - [j116]Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato:
normflows: A PyTorch Package for Normalizing Flows. J. Open Source Softw. 8(87): 5361 (2023) - [j115]R. Patrick Xian, Vincent Stimper, Marios Zacharias, Maciej Dendzik, Shuo Dong, Samuel Beaulieu, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, Ralph Ernstorfer:
A machine learning route between band mapping and band structure. Nat. Comput. Sci. 3(1): 101-114 (2023) - [j114]Armin Kekic, Jonas Dehning, Luigi Gresele, Julius von Kügelgen, Viola Priesemann, Bernhard Schölkopf:
Evaluating vaccine allocation strategies using simulation-assisted causal modeling. Patterns 4(6): 100739 (2023) - [j113]Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Samir Bhatt, Bernhard Schölkopf, Stefan Bauer:
Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases. PLoS Comput. Biol. 19(1) (2023) - [j112]Olga Mineeva, Daniel Danciu, Bernhard Schölkopf, Ruth E. Ley, Gunnar Rätsch, Nicholas D. Youngblut:
ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning. PLoS Comput. Biol. 19(5) (2023) - [j111]Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio:
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023) - [j110]Anson Lei, Bernhard Schölkopf, Ingmar Posner:
Variational Causal Dynamics: Discovering Modular World Models from Interventions. Trans. Mach. Learn. Res. 2023 (2023) - [j109]Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel:
Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. 2023 (2023) - [c426]Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan:
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. ACL (1) 2023: 545-561 - [c425]Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick:
Membership Inference Attacks against Language Models via Neighbourhood Comparison. ACL (Findings) 2023: 11330-11343 - [c424]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS 2023: 1411-1436 - [c423]Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf:
Iterative Teaching by Data Hallucination. AISTATS 2023: 9892-9913 - [c422]Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence:
Dataflow graphs as complete causal graphs. CAIN 2023: 7-12 - [c421]Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf:
Unsupervised Object Learning via Common Fate. CLeaR 2023: 281-327 - [c420]Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf:
On the Interventional Kullback-Leibler Divergence. CLeaR 2023: 328-349 - [c419]Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello:
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR 2023: 553-573 - [c418]Fernando Gonzalez Adauto, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea:
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. EMNLP (Findings) 2023: 415-438 - [c417]Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi:
Robustness Implies Fairness in Causal Algorithmic Recourse. FAccT 2023: 984-1001 - [c416]Max-Olivier Van Bastelaer, Heiner Kremer, Valentin Volchkov, Jean-Claude Passy, Bernhard Schölkopf:
Glare Removal for Astronomical Images with High Local Dynamic Range. ICCP 2023: 1-11 - [c415]Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Pairwise Similarity Learning is SimPLE. ICCV 2023: 5285-5295 - [c414]Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf:
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. ICLR 2023 - [c413]Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius:
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. ICLR 2023 - [c412]Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf:
Structure by Architecture: Structured Representations without Regularization. ICLR 2023 - [c411]Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf:
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. ICLR 2023 - [c410]Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato:
Flow Annealed Importance Sampling Bootstrap. ICLR 2023 - [c409]Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello:
Bridging the Gap to Real-World Object-Centric Learning. ICLR 2023 - [c408]Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel:
Provably Learning Object-Centric Representations. ICML 2023: 3038-3062 - [c407]Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf:
On Data Manifolds Entailed by Structural Causal Models. ICML 2023: 8188-8201 - [c406]Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx:
On the Identifiability and Estimation of Causal Location-Scale Noise Models. ICML 2023: 14316-14332 - [c405]Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf:
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. ICML 2023: 14333-14352 - [c404]Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim:
On the Relationship Between Explanation and Prediction: A Causal View. ICML 2023: 15861-15883 - [c403]Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F. Grewe, Bernhard Schölkopf:
Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions. ICML 2023: 16190-16215 - [c402]Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu:
Estimation Beyond Data Reweighting: Kernel Method of Moments. ICML 2023: 17745-17783 - [c401]Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou:
Diffusion Based Representation Learning. ICML 2023: 24963-24982 - [c400]Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf:
The Hessian perspective into the Nature of Convolutional Neural Networks. ICML 2023: 31930-31968 - [c399]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. ICML 2023: 34431-34455 - [c398]Alexander Dittrich, Jan Schneider, Simon Guist, Nico Gürtler, Heiko Ott, Thomas Steinbrenner, Bernhard Schölkopf, Dieter Büchler:
AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation. ICRA 2023: 3058-3064 - [c397]Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. IROS 2023: 567-573 - [c396]Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf:
Learning Locomotion Skills from MPC in Sensor Space. L4DC 2023: 1218-1230 - [c395]Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing.