Bernhard Schlkopf
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
305
Venues
46
Active years
1995–2026
Best venue rank
A*
Where they publish
- A*ICML78 papers
- A*ICLR49 papers
- AUAI26 papers
- AAISTATS21 papers
- A*CVPR12 papers
- A*EMNLP11 papers
- A*ACL9 papers
- A*ICCV9 papers
- AIROS6 papers
- A*AAAI6 papers
- A*ECCV6 papers
- A*COLT5 papers
- CICANN5 papers
- BICIP4 papers
- A*ICRA4 papers
- BSMC4 papers
- A*KDD4 papers
- ANAACL3 papers
- BICCP3 papers
- AEACL2 papers
- UnrankedCoRL2 papers
- A*ICDM2 papers
- A*IJCAI2 papers
- BESANN2 papers
- BALT2 papers
- AISMB2 papers
- NationalIWANN2 papers
- BIJCNLP1 paper
- CNeSy1 paper
- BCAIN1 paper
- A*CHI1 paper
- BGI1 paper
- A*WWW1 paper
- BACCV1 paper
- AMICCAI1 paper
- AICWSM1 paper
- MulticonferenceICASSP1 paper
- BISIT1 paper
- BRECOMB1 paper
- NationalKI1 paper
- ADIS1 paper
- NationalISAIM1 paper
- CECCB1 paper
- BICTAI1 paper
- BIJCNN1 paper
- BPAKDD1 paper
Papers
Showing the 300 most recent indexed papers.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | On the Emergence and Test-Time Use of Structural Information in Large Language Models. | Michelle Chao Chen, Moritz Miller, Bernhard Schlkopf, Siyuan Guo |
| 2026 | ACL | PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers in Overleaf. | Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner, Xuanqiang Angelo Huang, Vilm Zouhar, Dominik Glandorf, Isabel Dahlgren, Rishit Dagli, Yuen Chen, Felix Leeb, Van Q. Truong, Punya Syon Pandey, Yves Bicker, Suvajit Majumder, Wenyuan Jiang, Zeju Qiu, Sankalan Pal Chowdhury, Mrinmaya Sachan, Bernhard Schlkopf, Mona T. Diab, Zhijing Jin |
| 2026 | ACL | Test of Time: Rethinking Temporal Signal of Benchmark Contamination. | Terry Jingchen Zhang, Gopal Dev, Ning Wang, Max Obreiter, Wenyuan Jiang, Punya Syon Pandey, Keenan Samway, Yinya Huang, Bernhard Schlkopf, Mrinmaya Sachan, Zhijing Jin |
| 2026 | EACL | How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing Capabilities. | Aly M. Kassem, Bernhard Schlkopf, Zhijing Jin |
| 2026 | EACL | When Do Language Models Endorse Limitations on Human Rights Principles? | Keenan Samway, Miu Nicole Takagi, Rada Mihalcea, Bernhard Schlkopf, Ilias Chalkidis, Daniel Hershcovich, Zhijing Jin |
| 2025 | ACL | DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal. | Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, Zhijing Jin, Bernhard Schlkopf |
| 2025 | AISTATS | 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 Schlkopf |
| 2025 | EMNLP | Orthogonal Finetuning Made Scalable. | Zeju Qiu, Weiyang Liu, Adrian Weller, Bernhard Schlkopf |
| 2025 | EMNLP | Are Language Models Consequentialist or Deontological Moral Reasoners? | Keenan Samway, Max Kleiman-Weiner, David Guzman Piedrahita, Rada Mihalcea, Bernhard Schlkopf, Zhijing Jin |
| 2025 | EMNLP | Improving Large Language Model Safety with Contrastive Representation Learning. | Samuel Simko, Mrinmaya Sachan, Bernhard Schlkopf, Zhijing Jin |
| 2025 | ICIP | RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-Plane Networks. | Partha Ghosh, Soubhik Sanyal, Cordelia Schmid, Bernhard Schlkopf |
| 2025 | ICLR | Language Model Alignment in Multilingual Trolley Problems. | Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, Andrs Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schlkopf |
| 2025 | ICLR | Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. | Klaus-Rudolf Kladny, Bernhard Schlkopf, Michael Muehlebach |
| 2025 | ICLR | MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. | Andreas Opedal, Haruki Shirakami, Bernhard Schlkopf, Abulhair Saparov, Mrinmaya Sachan |
| 2025 | ICLR | Standardizing Structural Causal Models. | Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schlkopf, Andreas Krause |
| 2025 | ICLR | Preference Elicitation for Offline Reinforcement Learning. | Alize Pace, Bernhard Schlkopf, Gunnar Rtsch, Giorgia Ramponi |
| 2025 | ICLR | 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 Schlkopf |
| 2025 | ICLR | Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. | Patrik Reizinger, Siyuan Guo, Ferenc Huszr, Bernhard Schlkopf, Wieland Brendel |
| 2025 | ICLR | The Directionality of Optimization Trajectories in Neural Networks. | Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schlkopf |
| 2025 | ICML | Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models. | Armin Kekic, Sergio Hernan Garrido Mejia, Bernhard Schlkopf |
| 2025 | ICML | Generalized Interpolating Discrete Diffusion. | Dimitri von Rtte, Janis Fluri, Yuhui Ding, Antonio Orvieto, Bernhard Schlkopf, Thomas Hofmann |
| 2025 | ICML | Generative Intervention Models for Causal Perturbation Modeling. | Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schlkopf, Andreas Krause |
| 2025 | IJCNLP | Quriosity: Analyzing Human Questioning Behavior and Causal Inquiry through Curiosity-Driven Queries. | Roberto Ceraolo, Dmitrii Kharlapenko, Ahmad Khan, Amlie Reymond, Rada Mihalcea, Bernhard Schlkopf, Mrinmaya Sachan, Zhijing Jin |
| 2024 | ACL | CausalCite: A Causal Formulation of Paper Citations. | Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schlkopf |
| 2024 | ACL | Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. | Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schlkopf |
| 2024 | ACL | Mosai: Efficient Text-to-Music Diffusion Models. | Flavio Schneider, Ojasv Kamal, Zhijing Jin, Bernhard Schlkopf |
| 2024 | AISTATS | Causal Modeling with Stationary Diffusions. | Lars Lorch, Andreas Krause, Bernhard Schlkopf |
| 2024 | CoRL | 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 Schlkopf, Joni Pajarinen, Dieter Bchler |
| 2024 | CVPR | GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs. | Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schlkopf |
| 2024 | EMNLP | Implicit Personalization in Language Models: A Systematic Study. | Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schlkopf, Rada Mihalcea, Mrinmaya Sachan |
| 2024 | EMNLP | The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. | Shaobo Cui, Zhijing Jin, Bernhard Schlkopf, Boi Faltings |
| 2024 | EMNLP | Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis. | Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez Adauto, Rada Mihalcea, Bernhard Schlkopf, Mrinmaya Sachan |
| 2024 | ICLR | Out-of-Variable Generalisation for Discriminative Models. | Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schlkopf |
| 2024 | ICLR | Can Large Language Models Infer Causation from Correlation? | Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schlkopf |
| 2024 | ICLR | 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 Schlkopf |
| 2024 | ICLR | 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 Schlkopf |
| 2024 | ICLR | Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. | Alize Pace, Hugo Yche, Bernhard Schlkopf, Gunnar Rtsch, Guy Tennenholtz |
| 2024 | ICLR | Skill or Luck? Return Decomposition via Advantage Functions. | Hsiao-Ru Pan, Bernhard Schlkopf |
| 2024 | ICLR | Identifying Policy Gradient Subspaces. | Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Haeufle, Bernhard Schlkopf, Dieter Bchler |
| 2024 | ICLR | The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. | Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schlkopf, Anna Levina |
| 2024 | ICML | Robustness of Nonlinear Representation Learning. | Simon Buchholz, Bernhard Schlkopf |
| 2024 | ICML | Provable Privacy with Non-Private Pre-Processing. | Yaxi Hu, Amartya Sanyal, Bernhard Schlkopf |
| 2024 | ICML | Geometry-Aware Instrumental Variable Regression. | Heiner Kremer, Bernhard Schlkopf |
| 2024 | ICML | 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 Schlkopf, Abulhair Saparov, Mrinmaya Sachan |
| 2024 | ICML | Detecting and Identifying Selection Structure in Sequential Data. | Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schlkopf, Kun Zhang |
| 2024 | ICRA | Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. | 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 E. 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 Schlkopf, 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 Bchler, 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 T. 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, Joo Silvrio, 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 Snderhauf, 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 Martn-Martn, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, 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 |
| 2024 | NAACL | Analyzing the Role of Semantic Representations in the Era of Large Language Models. | Zhijing Jin, Yuen Chen, Fernando Gonzalez Adauto, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schlkopf, Mona T. Diab |
| 2024 | NAACL | A diverse Multilingual News Headlines Dataset from around the World. | Felix Leeb, Bernhard Schlkopf |
| 2024 | NeSy | Terminating Differentiable Tree Experts. | Jonathan Thomm, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzic, Bernhard Schlkopf, Abbas Rahimi |
| 2024 | UAI | Products, Abstractions and Inclusions of Causal Spaces. | Simon Buchholz, Junhyung Park, Bernhard Schlkopf |
| 2024 | UAI | Targeted Reduction of Causal Models. | Armin Kekic, Bernhard Schlkopf, Michel Besserve |
| 2023 | ACL | Membership Inference Attacks against Language Models via Neighbourhood Comparison. | Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schlkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick |
| 2023 | ACL | A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. | Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schlkopf, Mrinmaya Sachan |
| 2023 | AISTATS | BaCaDI: Bayesian Causal Discovery with Unknown Interventions. | Alexander Hgele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schlkopf, Andreas Krause |
| 2023 | AISTATS | Iterative Teaching by Data Hallucination. | Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schlkopf |
| 2023 | CAIN | Dataflow graphs as complete causal graphs. | Andrei Paleyes, Siyuan Guo, Bernhard Schlkopf, Neil D. Lawrence |
| 2023 | EMNLP | Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. | Fernando Gonzalez Adauto, Zhijing Jin, Bernhard Schlkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea |
| 2023 | ICCP | Glare Removal for Astronomical Images with High Local Dynamic Range. | Max-Olivier Van Bastelaer, Heiner Kremer, Valentin Volchkov, Jean-Claude Passy, Bernhard Schlkopf |
| 2023 | ICCV | Pairwise Similarity Learning is SimPLE. | Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schlkopf |
| 2023 | ICLR | DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. | Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kgelgen, Armin Kekic, Frederik Truble, Andrea Dittadi, Bernhard Schlkopf |
| 2023 | ICLR | Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. | Nico Grtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schlkopf, Georg Martius |
| 2023 | ICLR | Structure by Architecture: Structured Representations without Regularization. | Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schlkopf |
| 2023 | ICLR | Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. | Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schlkopf |
| 2023 | ICLR | Flow Annealed Importance Sampling Bootstrap. | Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schlkopf, Jos Miguel Hernndez-Lobato |
| 2023 | ICLR | 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 Schlkopf, Thomas Brox, Francesco Locatello |
| 2023 | ICML | Provably Learning Object-Centric Representations. | Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schlkopf, Julius von Kgelgen, Wieland Brendel |
| 2023 | ICML | On Data Manifolds Entailed by Structural Causal Models. | Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schlkopf |
| 2023 | ICML | Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. | Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rtsch, Bernhard Schlkopf |
| 2023 | ICML | On the Identifiability and Estimation of Causal Location-Scale Noise Models. | Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schlkopf, Peter Bhlmann, Alexander Marx |
| 2023 | ICML | On the Relationship Between Explanation and Prediction: A Causal View. | Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schlkopf, Been Kim |
| 2023 | ICML | Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions. | Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F. Grewe, Bernhard Schlkopf |
| 2023 | ICML | Estimation Beyond Data Reweighting: Kernel Method of Moments. | Heiner Kremer, Yassine Nemmour, Bernhard Schlkopf, Jia-Jie Zhu |
| 2023 | ICML | Diffusion Based Representation Learning. | Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schlkopf, Arash Mehrjou |
| 2023 | ICML | The Hessian perspective into the Nature of Convolutional Neural Networks. | Sidak Pal Singh, Thomas Hofmann, Bernhard Schlkopf |
| 2023 | ICML | Discrete Key-Value Bottleneck. | Frederik Truble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schlkopf |
| 2023 | ICRA | AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation. | Alexander Dittrich, Jan Schneider, Simon Guist, Nico Grtler, Heiko Ott, Thomas Steinbrenner, Bernhard Schlkopf, Dieter Bchler |
| 2023 | IROS | Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. | Philip Tobuschat, Hao Ma, Dieter Bchler, Bernhard Schlkopf, Michael Muehlebach |
| 2023 | UAI | Causal effect estimation from observational and interventional data through matrix weighted linear estimators. | Klaus-Rudolf Kladny, Julius von Kgelgen, Bernhard Schlkopf, Michael Muehlebach |
| 2022 | AAAI | On the Fairness of Causal Algorithmic Recourse. | Julius von Kgelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schlkopf |
| 2022 | AISTATS | A prior-based approximate latent Riemannian metric. | Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schlkopf |
| 2022 | AISTATS | A Witness Two-Sample Test. | Jonas M. Kbler, Wittawat Jitkrittum, Bernhard Schlkopf, Krikamol Muandet |
| 2022 | AISTATS | 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 Schlkopf |
| 2022 | AISTATS | Resampling Base Distributions of Normalizing Flows. | Vincent Stimper, Bernhard Schlkopf, Jos Miguel Hernndez-Lobato |
| 2022 | AISTATS | Adversarially Robust Kernel Smoothing. | Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schlkopf |
| 2022 | CVPR | Towards Total Recall in Industrial Anomaly Detection. | Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schlkopf, Thomas Brox, Peter V. Gehler |
| 2022 | CVPR | Towards Principled Disentanglement for Domain Generalization. | Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schlkopf, Eric P. Xing |
| 2022 | CVPR | Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. | Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthus Kleindessner, Francesco Locatello, Bernhard Schlkopf, Chris Russell |
| 2022 | ECCV | Structural Causal 3D Reconstruction. | Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schlkopf |
| 2022 | EMNLP | Logical Fallacy Detection. | Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schlkopf |
| 2022 | EMNLP | Differentially Private Language Models for Secure Data Sharing. | Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schlkopf, Mrinmaya Sachan |
| 2022 | ICLR | Group equivariant neural posterior estimation. | Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schlkopf, Jakob H. Macke |
| 2022 | ICLR | Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. | Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schlkopf |
| 2022 | ICLR | Invariant Causal Representation Learning for Out-of-Distribution Generalization. | Chaochao Lu, Yuhuai Wu, Jos Miguel Hernndez-Lobato, Bernhard Schlkopf |
| 2022 | ICLR | You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. | Osama Makansi, Julius von Kgelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schlkopf |
| 2022 | ICLR | Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. | Lukas Schott, Julius von Kgelgen, Frederik Truble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schlkopf, Francesco Locatello, Wieland Brendel |
| 2022 | ICLR | Phenomenology of Double Descent in Finite-Width Neural Networks. | Sidak Pal Singh, Aurlien Lucchi, Thomas Hofmann, Bernhard Schlkopf |
| 2022 | ICLR | The Role of Pretrained Representations for the OOD Generalization of RL Agents. | Frederik Truble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schlkopf, Stefan Bauer |
| 2022 | ICLR | Adversarial Robustness Through the Lens of Causality. | Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schlkopf, Kun Zhang |
| 2022 | ICML | Generalization and Robustness Implications in Object-Centric Learning. | Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schlkopf, Ole Winther, Francesco Locatello |
| 2022 | ICML | On the Adversarial Robustness of Causal Algorithmic Recourse. | Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Bernhard Schlkopf |
| 2022 | ICML | Causal Inference Through the Structural Causal Marginal Problem. | Luigi Gresele, Julius von Kgelgen, Jonas M. Kbler, Elke Kirschbaum, Bernhard Schlkopf, Dominik Janzing |
| 2022 | ICML | Action-Sufficient State Representation Learning for Control with Structural Constraints. | Biwei Huang, Chaochao Lu, Liu Leqi, Jos Miguel Hernndez-Lobato, Clark Glymour, Bernhard Schlkopf, Kun Zhang |
| 2022 | ICML | Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions. | Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schlkopf |
| 2022 | ICML | Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. | Paul Rolland, Volkan Cevher, Matthus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schlkopf, Francesco Locatello |
| 2022 | NAACL | Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. | Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schlkopf |
| 2022 | UAI | Learning soft interventions in complex equilibrium systems. | Michel Besserve, Bernhard Schlkopf |
| 2021 | AAAI | A Theory of Independent Mechanisms for Extrapolation in Generative Models. | Michel Besserve, Rmy Sun, Dominik Janzing, Bernhard Schlkopf |
| 2021 | AISTATS | Geometrically Enriched Latent Spaces. | Georgios Arvanitidis, Sren Hauberg, Bernhard Schlkopf |
| 2021 | AISTATS | Learning with Hyperspherical Uniformity. | Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schlkopf, Adrian Weller |
| 2021 | AISTATS | Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. | Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schlkopf |
| 2021 | EMNLP | Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. | Zhijing Jin, Julius von Kgelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schlkopf |
| 2021 | EMNLP | Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States. | Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schlkopf, Rada Mihalcea |
| 2021 | ICLR | CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. | Ossama Ahmed, Frederik Truble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schlkopf, Stefan Bauer |
| 2021 | ICLR | Predicting Infectiousness for Proactive Contact Tracing. | Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Mller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gatan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schlkopf, Abhinav Sharma, Jian Tang, Andrew Williams |
| 2021 | ICLR | On the Transfer of Disentangled Representations in Realistic Settings. | Andrea Dittadi, Frederik Truble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schlkopf |
| 2021 | ICLR | Recurrent Independent Mechanisms. | Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schlkopf |
| 2021 | ICLR | Fast And Slow Learning Of Recurrent Independent Mechanisms. | Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schlkopf, Yoshua Bengio |
| 2021 | ICLR | A teacher-student framework to distill future trajectories. | Alexander Neitz, Giambattista Parascandolo, Bernhard Schlkopf |
| 2021 | ICLR | Learning explanations that are hard to vary. | Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schlkopf |
| 2021 | ICLR | Spatially Structured Recurrent Modules. | Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schlkopf |
| 2021 | ICML | Bayesian Quadrature on Riemannian Data Manifolds. | Christian Frhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schlkopf, Georgios Arvanitidis |
| 2021 | ICML | Function Contrastive Learning of Transferable Meta-Representations. | Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schlkopf |
| 2021 | ICML | Necessary and sufficient conditions for causal feature selection in time series with latent common causes. | Atalanti-Anastasia Mastakouri, Bernhard Schlkopf, Dominik Janzing |
| 2021 | ICML | Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression. | Junhyung Park, Uri Shalit, Bernhard Schlkopf, Krikamol Muandet |
| 2021 | ICML | Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning. | Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schlkopf |
| 2021 | ICML | On Disentangled Representations Learned from Correlated Data. | Frederik Truble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schlkopf, Stefan Bauer |
| 2020 | AAAI | A Commentary on the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2020 | AAAI | ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. | Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schlkopf, Andreas Krause, Stefan Bauer |
| 2020 | AISTATS | Fair Decisions Despite Imperfect Predictions. | Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schlkopf, Krikamol Muandet, Isabel Valera |
| 2020 | CoRL | 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 Schlkopf, Stefan Bauer |
| 2020 | ICLR | Counterfactuals uncover the modular structure of deep generative models. | Michel Besserve, Arash Mehrjou, Rmy Sun, Bernhard Schlkopf |
| 2020 | ICLR | From Variational to Deterministic Autoencoders. | Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schlkopf |
| 2020 | ICLR | Disentangling Factors of Variations Using Few Labels. | Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem |
| 2020 | ICML | Towards Causal Algorithmic Recourse. | Amir-Hossein Karimi, Julius von Kgelgen, Bernhard Schlkopf, Isabel Valera |
| 2020 | ICML | Weakly-Supervised Disentanglement Without Compromises. | Francesco Locatello, Ben Poole, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem, Michael Tschannen |
| 2020 | ICRA | A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. | Diego Agudelo-Espaa, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schlkopf, Stefan Bauer, Manuel Wthrich |
| 2020 | UAI | Bayesian Online Prediction of Change Points. | Diego Agudelo-Espaa, Sebastin Gmez-Gonzlez, Stefan Bauer, Bernhard Schlkopf, Jan Peters |
| 2020 | UAI | Testing Goodness of Fit of Conditional Density Models with Kernels. | Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schlkopf |
| 2020 | UAI | Semi-supervised learning, causality, and the conditional cluster assumption. | Julius von Kgelgen, Alexander Mey, Marco Loog, Bernhard Schlkopf |
| 2020 | UAI | On the design of consequential ranking algorithms. | Behzad Tabibian, Vicen Gmez, Abir De, Bernhard Schlkopf, Manuel Gomez Rodriguez |
| 2019 | CHI | MYND: A Platform for Large-scale Neuroscientific Studies. | Matthias R. Hohmann, Michelle Hackl, Brian Wirth, Talha Zaman, Raffi Enficiaud, Moritz Grosse-Wentrup, Bernhard Schlkopf |
| 2019 | GI | Learning causal mechanisms. | Bernhard Schlkopf |
| 2019 | ICLR | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | ICLR | Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. | ore Miladinovic, Muhammad Waleed Gondal, Bernhard Schlkopf, Joachim M. Buhmann, Stefan Bauer |
| 2019 | ICML | AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. | Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schlkopf, Stefan Bauer |
| 2019 | ICML | Kernel Mean Matching for Content Addressability of GANs. | Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schlkopf |
| 2019 | ICML | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | ICML | First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. | Carl-Johann Simon-Gabriel, Yann Ollivier, Lon Bottou, Bernhard Schlkopf, David Lopez-Paz |
| 2019 | ICML | Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness. | Raphael Suter, ore Miladinovic, Bernhard Schlkopf, Stefan Bauer |
| 2019 | SMC | Neural Signatures of Motor Skill in the Resting Brain. | Ozan zdenizci, Timm Meyer, Felix A. Wichmann, Jan Peters, Bernhard Schlkopf, Mjdat etin, Moritz Grosse-Wentrup |
| 2019 | UAI | Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory. | Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schlkopf |
| 2019 | UAI | The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA. | Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schlkopf |
| 2018 | AISTATS | Group invariance principles for causal generative models. | Michel Besserve, Naji Shajarisales, Bernhard Schlkopf, Dominik Janzing |
| 2018 | AISTATS | Cause-Effect Inference by Comparing Regression Errors. | Patrick Blbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schlkopf |
| 2018 | ECCV | The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution. | Muhammad Waleed Gondal, Bernhard Schlkopf, Michael Hirsch |
| 2018 | ECCV | Spatio-Temporal Transformer Network for Video Restoration. | Tae Hyun Kim, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Schlkopf |
| 2018 | ICCP | Automatic estimation of modulation transfer functions. | Matthias Bauer, Valentin Volchkov, Michael Hirsch, Bernhard Schlkopf |
| 2018 | ICLR | Fidelity-Weighted Learning. | Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schlkopf |
| 2018 | ICLR | Clustering Meets Implicit Generative Models. | Francesco Locatello, Damien Vincent, Ilya O. Tolstikhin, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf |
| 2018 | ICLR | Learning Disentangled Representations with Wasserstein Auto-Encoders. | Paul K. Rubenstein, Bernhard Schlkopf, Ilya O. Tolstikhin |
| 2018 | ICLR | Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders. | Paul K. Rubenstein, Bernhard Schlkopf, Ilya O. Tolstikhin |
| 2018 | ICLR | Tempered Adversarial Networks. | Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schlkopf |
| 2018 | ICLR | Wasserstein Auto-Encoders. | Ilya O. Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schlkopf |
| 2018 | ICML | Differentially Private Database Release via Kernel Mean Embeddings. | Matej Balog, Ilya O. Tolstikhin, Bernhard Schlkopf |
| 2018 | ICML | Detecting non-causal artifacts in multivariate linear regression models. | Dominik Janzing, Bernhard Schlkopf |
| 2018 | ICML | On Matching Pursuit and Coordinate Descent. | Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rtsch, Bernhard Schlkopf, Sebastian U. Stich, Martin Jaggi |
| 2018 | ICML | Learning Independent Causal Mechanisms. | Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schlkopf |
| 2018 | ICML | Tempered Adversarial Networks. | Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schlkopf |
| 2018 | KDD | Generalized Score Functions for Causal Discovery. | Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schlkopf, Clark Glymour |
| 2018 | UAI | From Deterministic ODEs to Dynamic Structural Causal Models. | Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schlkopf |
| 2017 | AISTATS | Local Group Invariant Representations via Orbit Embeddings. | Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schlkopf |
| 2017 | CVPR | Discovering Causal Signals in Images. | David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schlkopf, Lon Bottou |
| 2017 | CVPR | Flexible Spatio-Temporal Networks for Video Prediction. | Chaochao Lu, Michael Hirsch, Bernhard Schlkopf |
| 2017 | ICCV | Online Video Deblurring via Dynamic Temporal Blending Network. | Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schlkopf, Michael Hirsch |
| 2017 | ICCV | EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis. | Mehdi S. M. Sajjadi, Bernhard Schlkopf, Michael Hirsch |
| 2017 | ICCV | Learning Blind Motion Deblurring. | Patrick Wieschollek, Michael Hirsch, Bernhard Schlkopf, Hendrik P. A. Lensch |
| 2017 | ICDM | Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. | Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schlkopf |
| 2017 | IJCAI | Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. | Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schlkopf |
| 2017 | SMC | Personalized brain-computer interface models for motor rehabilitation. | Anastasia-Atalanti Mastakouri, Sebastian Weichwald, Ozan zdenizci, Timm Meyer, Bernhard Schlkopf, Moritz Grosse-Wentrup |
| 2017 | WWW | Distilling Information Reliability and Source Trustworthiness from Digital Traces. | Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schlkopf, Manuel Gomez-Rodriguez |
| 2017 | UAI | Causal Discovery from Temporally Aggregated Time Series. | Mingming Gong, Kun Zhang, Bernhard Schlkopf, Clark Glymour, Dacheng Tao |
| 2017 | UAI | Causal Consistency of Structural Equation Models. | Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schlkopf |
| 2016 | ACCV | End-to-End Learning for Image Burst Deblurring. | Patrick Wieschollek, Bernhard Schlkopf, Hendrik P. A. Lensch, Michael Hirsch |
| 2016 | ICML | The Arrow of Time in Multivariate Time Series. | Stefan Bauer, Bernhard Schlkopf, Jonas Peters |
| 2016 | ICML | Domain Adaptation with Conditional Transferable Components. | Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schlkopf |
| 2016 | UAI | On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. | Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schlkopf, Clark Glymour |
| 2015 | AAAI | Multi-Source Domain Adaptation: A Causal View. | Kun Zhang, Mingming Gong, Bernhard Schlkopf |
| 2015 | AISTATS | Inference of Cause and Effect with Unsupervised Inverse Regression. | Eleni Sgouritsa, Dominik Janzing, Philipp Hennig, Bernhard Schlkopf |
| 2015 | ICCV | Self-Calibration of Optical Lenses. | Michael Hirsch, Bernhard Schlkopf |
| 2015 | ICML | Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components. | Philipp Geiger, Kun Zhang, Bernhard Schlkopf, Mingming Gong, Dominik Janzing |
| 2015 | ICML | Discovering Temporal Causal Relations from Subsampled Data. | Mingming Gong, Kun Zhang, Bernhard Schlkopf, Dacheng Tao, Philipp Geiger |
| 2015 | ICML | Retrospective Motion Correction of Magnitude-Input MR Images. | Alexander Loktyushin, Christian J. Schuler, Klaus Scheffler, Bernhard Schlkopf |
| 2015 | ICML | Towards a Learning Theory of Cause-Effect Inference. | David Lopez-Paz, Krikamol Muandet, Bernhard Schlkopf, Ilya O. Tolstikhin |
| 2015 | ICML | Removing systematic errors for exoplanet search via latent causes. | Bernhard Schlkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters |
| 2015 | ICML | Telling cause from effect in deterministic linear dynamical systems. | Naji Shajarisales, Dominik Janzing, Bernhard Schlkopf, Michel Besserve |
| 2015 | IJCAI | Identification of Time-Dependent Causal Model: A Gaussian Process Treatment. | Biwei Huang, Kun Zhang, Bernhard Schlkopf |
| 2015 | IROS | Learning optimal striking points for a ping-pong playing robot. | Yanlong Huang, Bernhard Schlkopf, Jan Peters |
| 2015 | MICCAI | BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease. | Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schlkopf, Thomas Schultz |
| 2015 | SMC | A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis. | Matthias R. Hohmann, Tatiana Fomina, Vinay Jayaram, Natalie Widmann, Christian Forster, Jennifer Muller vom Hagen, Matthis Synofzik, Bernhard Schlkopf, Ludger Schls, Moritz Grosse-Wentrup |
| 2014 | AISTATS | Towards building a Crowd-Sourced Sky Map. | Dustin Lang, David W. Hogg, Bernhard Schlkopf |
| 2014 | COLT | Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem. | Manuel Gomez-Rodriguez, Le Song, Bernhard Schlkopf |
| 2014 | CVPR | Seeing the Arrow of Time. | Lyndsey C. Pickup, Zheng Pan, Donglai Wei, Yi-Chang Shih, Changshui Zhang, Andrew Zisserman, Bernhard Schlkopf, William T. Freeman |
| 2014 | ICML | Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. | Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schlkopf |
| 2014 | ICML | Consistency of Causal Inference under the Additive Noise Model. | Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schlkopf |
| 2014 | ICML | Randomized Nonlinear Component Analysis. | David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schlkopf |
| 2014 | ICML | Kernel Mean Estimation and Stein Effect. | Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schlkopf |
| 2014 | ICWSM | Quantifying Information Overload in Social Media and Its Impact on Social Contagions. | Manuel Gomez-Rodriguez, Krishna P. Gummadi, Bernhard Schlkopf |
| 2014 | UAI | Inferring latent structures via information inequalities. | Rafael Chaves, Lukas Luft, Thiago O. Maciel, David Gross, Dominik Janzing, Bernhard Schlkopf |
| 2014 | UAI | A Permutation-Based Kernel Conditional Independence Test. | Gary Doran, Krikamol Muandet, Kun Zhang, Bernhard Schlkopf |
| 2014 | UAI | Estimating Causal Effects by Bounding Confounding. | Philipp Geiger, Dominik Janzing, Bernhard Schlkopf |
| 2013 | CVPR | 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 Schlkopf |
| 2013 | CVPR | A Machine Learning Approach for Non-blind Image Deconvolution. | Christian J. Schuler, Harold Christopher Burger, Stefan Harmeling, Bernhard Schlkopf |
| 2013 | ICDM | On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example. | Kun Zhang, Zhikun Wang, Bernhard Schlkopf |
| 2013 | ICIP | Improving alpha matting and motion blurred foreground estimation. | Rolf Khler, Michael Hirsch, Bernhard Schlkopf, Stefan Harmeling |
| 2013 | ICML | Modeling Information Propagation with Survival Theory. | Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schlkopf |
| 2013 | ICML | Domain Generalization via Invariant Feature Representation. | Krikamol Muandet, David Balduzzi, Bernhard Schlkopf |
| 2013 | ICML | Domain Adaptation under Target and Conditional Shift. | Kun Zhang, Bernhard Schlkopf, Krikamol Muandet, Zhikun Wang |
| 2013 | UAI | From Ordinary Differential Equations to Structural Causal Models: the deterministic case. | Joris M. Mooij, Dominik Janzing, Bernhard Schlkopf |
| 2013 | UAI | One-Class Support Measure Machines for Group Anomaly Detection. | Krikamol Muandet, Bernhard Schlkopf |
| 2013 | UAI | Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. | Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schlkopf |
| 2012 | ECCV | Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. | Rolf Khler, Michael Hirsch, Betty J. Mohler, Bernhard Schlkopf, Stefan Harmeling |
| 2012 | ECCV | Blind Correction of Optical Aberrations. | Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schlkopf |
| 2012 | ICIP | A blind deconvolution approach for pseudo CT prediction from MR image pairs. | Michael Hirsch, Matthias Hofmann, Frederic Mantlik, Bernd J. Pichler, Bernhard Schlkopf, Michael Habeck |
| 2012 | ICML | Influence Maximization in Continuous Time Diffusion Networks. | Manuel Gomez-Rodriguez, Bernhard Schlkopf |
| 2012 | ICML | Submodular Inference of Diffusion Networks from Multiple Trees. | Manuel Gomez-Rodriguez, Bernhard Schlkopf |
| 2012 | ICML | On causal and anticausal learning. | Bernhard Schlkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij |
| 2012 | IROS | A brain-robot interface for studying motor learning after stroke. | Timm Meyer, Jan Peters, Doris Brtz, Thorsten O. Zander, Bernhard Schlkopf, Surjo R. Soekadar, Moritz Grosse-Wentrup |
| 2011 | ICASSP | Finding dependencies between frequencies with the kernel cross-spectral density. | Michel Besserve, Dominik Janzing, Nikos K. Logothetis, Bernhard Schlkopf |
| 2011 | ICCP | Removing noise from astronomical images using a pixel-specific noise model. | Harold Christopher Burger, Bernhard Schlkopf, Stefan Harmeling |
| 2011 | ICCV | Fast removal of non-uniform camera shake. | Michael Hirsch, Christian J. Schuler, Stefan Harmeling, Bernhard Schlkopf |
| 2011 | ICCV | Non-stationary correction of optical aberrations. | Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schlkopf |
| 2011 | ICML | Support Vector Machines as Probabilistic Models. | Vojtech Franc, Alexander Zien, Bernhard Schlkopf |
| 2011 | ICML | Uncovering the Temporal Dynamics of Diffusion Networks. | Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schlkopf |
| 2011 | IROS | Learning inverse kinematics with structured prediction. | Botond Bocsi, Duy Nguyen-Tuong, Lehel Csat, Bernhard Schlkopf, Jan Peters |
| 2011 | IROS | Learning anticipation policies for robot table tennis. | Zhikun Wang, Christoph H. Lampert, Katharina Mlling, Bernhard Schlkopf, Jan Peters |
| 2011 | KDD | Two-locus association mapping in subquadratic time. | Panagiotis Achlioptas, Bernhard Schlkopf, Karsten M. Borgwardt |
| 2011 | UAI | Detecting low-complexity unobserved causes. | Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schlkopf |
| 2011 | UAI | Identifiability of Causal Graphs using Functional Models. | Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schlkopf |
| 2011 | UAI | Kernel-based Conditional Independence Test and Application in Causal Discovery. | Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schlkopf |
| 2010 | COLT | Causal Markov Condition for Submodular Information Measures. | Bastian Steudel, Dominik Janzing, Bernhard Schlkopf |
| 2010 | CVPR | Efficient filter flow for space-variant multiframe blind deconvolution. | Michael Hirsch, Suvrit Sra, Bernhard Schlkopf, Stefan Harmeling |
| 2010 | ICIP | Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. | Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bernhard Schlkopf |
| 2010 | ICML | Telling cause from effect based on high-dimensional observations. | Dominik Janzing, Patrik O. Hoyer, Bernhard Schlkopf |
| 2010 | ICRA | Movement templates for learning of hitting and batting. | Jens Kober, Katharina Mlling, Oliver Kroemer, Christoph H. Lampert, Bernhard Schlkopf, Jan Peters |
| 2010 | ISIT | Non-parametric estimation of integral probability metrics. | Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schlkopf, Gert R. G. Lanckriet |
| 2010 | RECOMB | A New Algorithm for Improving the Resolution of Cryo-EM Density Maps. | Michael Hirsch, Bernhard Schlkopf, Michael Habeck |
| 2010 | SMC | Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery. | Manuel Gomez-Rodriguez, Jan Peters, N. Jeremy Hill, Bernhard Schlkopf, Alireza Gharabaghi, Moritz Grosse-Wentrup |
| 2010 | UAI | Inferring deterministic causal relations. | Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schlkopf |
| 2010 | UAI | Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. | Kun Zhang, Bernhard Schlkopf, Dominik Janzing |
| 2009 | CVPR | Learning similarity measure for multi-modal 3D image registration. | Daewon Lee, Matthias Hofmann, Florian Steinke, Yasemin Altun, Nathan D. Cahill, Bernhard Schlkopf |
| 2009 | ICML | Regression by dependence minimization and its application to causal inference in additive noise models. | Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schlkopf |
| 2009 | ICML | Detecting the direction of causal time series. | Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schlkopf |
| 2009 | IROS | Sparse online model learning for robot control with support vector regression. | Duy Nguyen-Tuong, Bernhard Schlkopf, Jan Peters |
| 2009 | KDD | Multi-way set enumeration in real-valued tensors. | Elisabeth Georgii, Koji Tsuda, Bernhard Schlkopf |
| 2009 | KI | Generalized Clustering via Kernel Embeddings. | Stefanie Jegelka, Arthur Gretton, Bernhard Schlkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg |
| 2009 | UAI | Identifying confounders using additive noise models. | Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schlkopf |
| 2008 | COLT | Injective Hilbert Space Embeddings of Probability Measures. | Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schlkopf |
| 2008 | ECCV | Automatic Image Colorization Via Multimodal Predictions. | Guillaume Charpiat, Matthias Hofmann, Bernhard Schlkopf |
| 2008 | ESANN | Learning Inverse Dynamics: a Comparison. | Duy Nguyen-Tuong, Jan Peters, Matthias W. Seeger, Bernhard Schlkopf |
| 2008 | ICML | Tailoring density estimation via reproducing kernel moment matching. | Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schlkopf |
| 2008 | ICML | Sparse multiscale gaussian process regression. | Christian Walder, Kwang In Kim, Bernhard Schlkopf |
| 2007 | AAAI | A Kernel Approach to Comparing Distributions. | Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schlkopf, Alexander J. Smola |
| 2007 | ALT | A Hilbert Space Embedding for Distributions. | Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schlkopf |
| 2007 | DIS | A Hilbert Space Embedding for Distributions. | Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schlkopf |
| 2007 | ESANN | Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. | Xiaohai Sun, Dominik Janzing, Bernhard Schlkopf |
| 2007 | ICML | A kernel-based causal learning algorithm. | Xiaohai Sun, Dominik Janzing, Bernhard Schlkopf, Kenji Fukumizu |
| 2007 | ICML | Local learning projections. | Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schlkopf |
| 2006 | CVPR | Learning an Interest Operator from Human Eye Movements. | Wolf Kienzle, Felix A. Wichmann, Bernhard Schlkopf, Matthias O. Franz |
| 2006 | ISAIM | Causal Inference by Choosing Graphs with Most Plausible Markov Kernels. | Xiaohai Sun, Dominik Janzing, Bernhard Schlkopf |
| 2006 | ISMB | Integrating structured biological data by Kernel Maximum Mean Discrepancy. | Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schlkopf, Alexander J. Smola |
| 2005 | AISTATS | Kernel Constrained Covariance for Dependence Measurement. | Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schlkopf, Nikos K. Logothetis |
| 2005 | ALT | Measuring Statistical Dependence with Hilbert-Schmidt Norms. | Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schlkopf |
| 2005 | ECCB | Fast protein classification with multiple networks. | Koji Tsuda, Hyunjung Shin, Bernhard Schlkopf |
| 2005 | ICML | A brain computer interface with online feedback based on magnetoencephalography. | Thomas Navin Lal, Michael Schrder, N. Jeremy Hill, Hubert Preil, Thilo Hinterberger, Jrgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schlkopf |
| 2005 | ICML | Object correspondence as a machine learning problem. | Bernhard Schlkopf, Florian Steinke, Volker Blanz |
| 2005 | ICML | Large scale genomic sequence SVM classifiers. | Sren Sonnenburg, Gunnar Rtsch, Bernhard Schlkopf |
| 2005 | ICML | Implicit surface modelling as an eigenvalue problem. | Christian Walder, Olivier Chapelle, Bernhard Schlkopf |
| 2005 | ICML | Building Sparse Large Margin Classifiers. | Mingrui Wu, Bernhard Schlkopf, Gkhan H. Bakir |
| 2005 | ICML | Learning from labeled and unlabeled data on a directed graph. | Dengyong Zhou, Jiayuan Huang, Bernhard Schlkopf |
| 2005 | ISMB | RASE: recognition of alternatively spliced exons in | Gunnar Rtsch, Sren Sonnenburg, Bernhard Schlkopf |
| 2005 | IWANN | Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach. | Tobias Jung, Luis Javier Herrera, Bernhard Schlkopf |
| 2005 | IWANN | Joint Kernel Maps. | Jason Weston, Bernhard Schlkopf, Olivier Bousquet |
| 2004 | ICML | A kernel view of the dimensionality reduction of manifolds. | Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schlkopf |
| 2003 | ICTAI | Feature Selection for Support Vector Machines by Means of Genetic Algorithms. | Holger Frhlich, Olivier Chapelle, Bernhard Schlkopf |
| 2001 | AISTATS | An improved training algorithm for kernel Fisher discriminants. | Sebastian Mika, Alexander J. Smola, Bernhard Schlkopf |
| 2001 | AISTATS | A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds. | Michael E. Tipping, Bernhard Schlkopf |
| 2001 | COLT | A Generalized Representer Theorem. | Bernhard Schlkopf, Ralf Herbrich, Alexander J. Smola |
| 2001 | ICCV | Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation. | Stan Z. Li, QingDong Fu, Lie Gu, Bernhard Schlkopf, Yimin Cheng, HongJiang Zhang |
| 2001 | ICCV | Computationally Efficient Face Detection. | Sami Romdhani, Philip H. S. Torr, Bernhard Schlkopf, Andrew Blake |
| 2001 | ICML | Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. | Neil D. Lawrence, Bernhard Schlkopf |
| 2000 | COLT | Entropy Numbers of Linear Function Classes. | Robert C. Williamson, Alexander J. Smola, Bernhard Schlkopf |
| 2000 | ICML | Sparse Greedy Matrix Approximation for Machine Learning. | Alexander J. Smola, Bernhard Schlkopf |
| 2000 | IJCNN | Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. | Athanassia Chalimourda, Bernhard Schlkopf, Alexander J. Smola |
| 2000 | PAKDD | Robust Ensemble Learning for Data Mining. | Gunnar Rtsch, Bernhard Schlkopf, Alexander J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Mller |
| 1997 | ICANN | The View-Graph Approach to Visual Navigation and Spatial Memory. | Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schlkopf, Heinrich H. Blthoff |
| 1997 | ICANN | Predicting Time Series with Support Vector Machines. | Klaus-Robert Mller, Alexander J. Smola, Gunnar Rtsch, Bernhard Schlkopf, Jens Kohlmorgen, Vladimir Vapnik |
| 1997 | ICANN | Kernel Principal Component Analysis. | Bernhard Schlkopf, Alexander J. Smola, Klaus-Robert Mller |
| 1996 | ICANN | Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. | Volker Blanz, Bernhard Schlkopf, Heinrich H. Blthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter |
| 1996 | ICANN | Incorporating Invariances in Support Vector Learning Machines. | Bernhard Schlkopf, Chris Burges, Vladimir Vapnik |
| 1995 | KDD | Extracting Support Data for a Given Task. | Bernhard Schlkopf, Chris Burges, Vladimir Vapnik |