Andrussow, I., Sun, H., Martius, G., Kuchenbecker, K. J. Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

Project Page [BibTex]

Bonse, M. J., Gebhard, T. D., Dannert, F. A., Absil, O., Cantalloube, F., Christiaens, V., Cugno, G., Garvin, E. O., Hayoz, J., Kasper, M., Matthews, E., Schölkopf, B., Quanz, S. P. Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011 2024 (misc) Submitted

arXiv [BibTex]

Buchholz, S., Kübler, J. M., Schölkopf, B. Multi-Armed Bandits and Quantum Channel Oracles 2024 (misc)

arXiv [BibTex]

Rajendran, G., Buchholz, S., Aragam, B., Schölkopf, B., Ravikumar, P. Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models 2024 (misc)

arXiv [BibTex]

Jenny, D. Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures ETH Zurich, Switzerland, November 2023, external supervision (thesis)

[BibTex]

Jin, Z., Mihalcea, R. Natural Language Processing for Policymaking In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

DOI [BibTex]

Bottou, L., Schölkopf, B. Borges und die Künstliche Intelligenz 2023, published in Frankfurter Allgemeine Zeitung, 18 December 2023, Nr. 294 (misc)

PDF [BibTex]

Schölkopf, B. Causality, causal digital twins, and their applications Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382), (Editors: Berens, Philipp and Cranmer, Kyle and Lawrence, Neil D. and von Luxburg, Ulrike and Montgomery, Jessica), September 2022 (talk)

link (url) DOI [BibTex]

Wang, H., Jin, Z., Cao, J., Fung, G. P. C., Wong, K. Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning 2022 (misc)

arXiv [BibTex]

Peters, J., Bauer, S., Pfister, N. Causal Models for Dynamical Systems In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

arXiv DOI [BibTex]

Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. Towards Causal Algorithmic Recourse In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

DOI [BibTex]

Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z. CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

DOI [BibTex]

Schölkopf, B. Causality for Machine Learning In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

arXiv DOI [BibTex]

Prabhoo, S., Bauer, S., Schwab, P. NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments 2021 (misc)

arXiv [BibTex]

Abdulsamad, H., Dorau, T., Belousov, B., Zhu, J., Peters, J. Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions 2021 (misc)

arXiv Project Page [BibTex]

Arvanitidis, G., González Duque, M., Pouplin, A., Kalatzis, D., Hauberg, S. Pulling back information geometry 2021 (misc)

arXiv [BibTex]

Wüthrich*, M., Widmaier*, F., Bauer*, S., Funk, N., Urain, J., Peters, J., Watson, J., Chen, C., Srinivasan, K., Zhang, J., Zhang, J., Walter, M. R., Madan, R., Schaff, C., Maeda, T., Yoneda, T., Yarats, D., Allshire, A., Gordon, E. K., Bhattacharjee, T., Srinivasa, S. S., Garg, A., Buchholz, A., Stark, S., Steinbrenner, T., Akpo, J., Joshi, S., Agrawal, V., Schölkopf, B. A Robot Cluster for Reproducible Research in Dexterous Manipulation 2021, *equal contribution (misc)

arXiv [BibTex]

Belousov, B., H., A., Klink, P., Parisi, S., Peters, J. Reinforcement Learning Algorithms: Analysis and Applications 883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)

DOI [BibTex]

Shao, K., Villegas, J. F. R., Logothetis, N. K., Besserve, M. A model of Ponto-Geniculo-Occipital waves supports bidirectional control of cortical plasticity across sleep-stages 2021 (misc) In preparation

bioRxiv DOI [BibTex]

Georgiev, B., Franken, L., Mukherjee, M., Arvanitidis, G. On the Impact of Stable Ranks in Deep Nets 2021 (misc)

arXiv [BibTex]

Scientific Report 2016 - 2021 2021 (mpi_year_book)

Scientific Report 2016 - 2021 [BibTex]

Allshire, A., Mittal, M., Lodaya, V., Makoviychuk, V., Makoviichuk, D., Widmaier, F., Wüthrich, M., Bauer, S., Handa, A., Garg, A. Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger 2021 (misc)

arXiv [BibTex]

Chicharro, D., Besserve, M., Panzeri, S. Causal learning with sufficient statistics: an information bottleneck approach 2020 (misc) Submitted

arXiv [BibTex]

Träuble, F., Creager, E., Kilbertus, N., Goyal, A., Locatello, F., Schölkopf, B., Bauer, S. Is Independence all you need? On the Generalization of Representations Learned from Correlated Data 2020 (misc)

link (url) [BibTex]

Tosatto, S., Stadtmueller, J., Peters, J. Dimensionality Reduction of Movement Primitives in Parameter Space 2020 (misc)

arXiv [BibTex]

Besserve, M., Buchholz, S., Schölkopf, B. Assaying Large-scale Testing Models to Interpret Covid-19 Case Numbers. A Cross-country Study 2020 (misc) Submitted

arXiv [BibTex]

Ke, R., Bilaniuk, O., Goyal, A., Bauer, S., Larochelle, H., Schölkopf, B., Mozer, M. C., Pal, C., Bengio, Y. Learning Neural Causal Models from Unknown Interventions 2020 (misc)

arXiv Project Page [BibTex]

Safavi, S., Logothetis, N., Besserve, M. Multivariate coupling estimation between continuous signals and point processes Neural Information Processing Systems 2019 - Workshop on Learning with Temporal Point Processes, December 2019 (talk)

Talk video link (url) [BibTex]

Lutz, P. Automatic Segmentation and Labelling for Robot Table Tennis Time Series Technical University Darmstadt, Germany, August 2019 (thesis)

[BibTex]

Park, M., Jitkrittum, W. ABCDP: Approximate Bayesian Computation Meets Differential Privacy 2019 (misc) Submitted

arXiv [BibTex]

Scientific Report 2016 - 2018 2019 (mpi_year_book)

Scientific Report 2016 - 2018 [BibTex]

Pfister, N., Bauer, S., Peters, J. Identifying Causal Structure in Large-Scale Kinetic Systems 2019 (misc)

link (url) [BibTex]

Tanneberg, D., Rueckert, E., Peters, J. Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture 2019 (misc)

arXiv [BibTex]

Schölkopf, B. Die kybernetische Revolution S{\"u}ddeutsche Zeitung, 2018, (15-Mar-2018) (misc)

link (url) [BibTex]

Schölkopf, B. Maschinelles Lernen: Entwicklung ohne Grenzen? In Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)

[BibTex]

Wichmann, F. A., Jäkel, F. Methods in Psychophysics In Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (inbook)

[BibTex]

Veiga, F. F., Edin, B. B., Peters, J. In-Hand Object Stabilization by Independent Finger Control 2018 (misc)

arXiv [BibTex]

Jayaram, V., Fiebig, K., Peters, J., Grosse-Wentrup, M. Transfer Learning for BCIs In Brain–Computer Interfaces Handbook, pages: 425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (incollection)

[BibTex]

Garreau, D., Jitkrittum, W., Kanagawa, M. Large sample analysis of the median heuristic 2018 (misc) In preparation

arXiv [BibTex]

Weichwald, S., Grosse-Wentrup, M. The right tool for the right question — beyond the encoding versus decoding dichotomy 2017 (misc)

ArXiv PDF [BibTex]

Peters, J., Lee, D., Kober, J., Nguyen-Tuong, D., Bagnell, J., Schaal, S. Robot Learning In Springer Handbook of Robotics, pages: 357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (inbook)

[BibTex]

Peters, J., Janzing, D., Schölkopf, B. Elements of Causal Inference - Foundations and Learning Algorithms Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

PDF link (url) [BibTex]

Peters, J., Bagnell, J. Policy Gradient Methods In Encyclopedia of Machine Learning and Data Mining, pages: 982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

link (url) [BibTex]

Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L. Unsupervised clustering of EOG as a viable substitute for optical eye-tracking In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

DOI [BibTex]

Rubenstein, P. K., Tolstikhin, I., Hennig, P., Schölkopf, B. Probabilistic Active Learning of Functions in Structural Causal Models 2017 (misc)

Arxiv [BibTex]

Peters, J., Tedrake, R., Roy, N., Morimoto, J. Robot Learning In Encyclopedia of Machine Learning and Data Mining, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

DOI [BibTex]

Janzing, D. Statistical Asymmetries Between Cause and Effect In Time in Physics, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

link (url) DOI [BibTex]

Bousquet, O., Gelly, S., Tolstikhin, I., Simon-Gabriel, C. J., Schölkopf, B. From Optimal Transport to Generative Modeling: the VEGAN cookbook 2017 (misc)

arXiv follow-up paper [BibTex]

Belousov, B., Peters, J. f-Divergence constrained policy improvement 2017 (misc)

arXiv [BibTex]

Empirical Inference (2010-2015) Scientific Advisory Board Report, 2016 (misc)

pdf [BibTex]