2024
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
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
Rajendran, G., Buchholz, S., Aragam, B., Schölkopf, B., Ravikumar, P.
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models
2024 (misc)
2023
Jenny, D.
Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures
ETH Zurich, Switzerland, November 2023, external supervision (thesis)
Bottou, L., Schölkopf, B.
Borges und die Künstliche Intelligenz
2023, published in Frankfurter Allgemeine Zeitung, 18 December 2023, Nr. 294 (misc)
2022
Biester, L., Demszky, D., Jin, Z., Sachan, M., Tetreault, J., Wilson, S., Xiao, L., Zhao, J.
Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)
Association for Computational Linguistics, December 2022 (proceedings)
Schölkopf, B., Uhler, C., Zhang, K.
Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022)
177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)
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)
2021
Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C.
Proceedings of the 1st Workshop on NLP for Positive Impact
Association for Computational Linguistics, August 2021 (proceedings)
Prabhoo, S., Bauer, S., Schwab, P.
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments
2021 (misc)
Abdulsamad, H., Dorau, T., Belousov, B., Zhu, J., Peters, J.
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions
2021 (misc)
Arvanitidis, G., González Duque, M., Pouplin, A., Kalatzis, D., Hauberg, S.
Pulling back information geometry
2021 (misc)
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)
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)
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
Georgiev, B., Franken, L., Mukherjee, M., Arvanitidis, G.
On the Impact of Stable Ranks in Deep Nets
2021 (misc)
Scientific Report 2016 - 2021
2021 (mpi_year_book)
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)
2020
Chicharro, D., Besserve, M., Panzeri, S.
Causal learning with sufficient statistics: an information bottleneck approach
2020 (misc) Submitted
Tosatto, S., Stadtmueller, J., Peters, J.
Dimensionality Reduction of Movement Primitives in Parameter Space
2020 (misc)
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)
2019
Lutz, P.
Automatic Segmentation and Labelling for Robot Table Tennis Time Series
Technical University Darmstadt, Germany, August 2019 (thesis)
Park, M., Jitkrittum, W.
ABCDP: Approximate Bayesian Computation Meets Differential Privacy
2019 (misc) Submitted
Scientific Report 2016 - 2018
2019 (mpi_year_book)
Pfister, N., Bauer, S., Peters, J.
Identifying Causal Structure in Large-Scale Kinetic Systems
2019 (misc)
Tanneberg, D., Rueckert, E., Peters, J.
Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture
2019 (misc)
2018
Schölkopf, B.
Die kybernetische Revolution
S{\"u}ddeutsche Zeitung, 2018, (15-Mar-2018) (misc)
Veiga, F. F., Edin, B. B., Peters, J.
In-Hand Object Stabilization by Independent Finger Control
2018 (misc)
Garreau, D., Jitkrittum, W., Kanagawa, M.
Large sample analysis of the median heuristic
2018 (misc) In preparation
2017
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)
Bousquet, O., Gelly, S., Tolstikhin, I., Simon-Gabriel, C. J., Schölkopf, B.
From Optimal Transport to Generative Modeling: the VEGAN cookbook
2017 (misc)
Belousov, B., Peters, J.
f-Divergence constrained policy improvement
2017 (misc)
2016
Ihler, A. T., Janzing, D.
Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI)
pages: 869 pages, AUAI Press, June 2016 (proceedings)
Empirical Inference (2010-2015)
Scientific Advisory Board Report, 2016 (misc)
Mittal, A., Raj, A., Namboodiri, V. P., Tuytelaars, T.
Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set
2016 (misc)
2014
Kober, J., Peters, J.
Learning Motor Skills: From Algorithms to Robot Experiments
97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)
2013
Deisenroth, M., Szepesvári, C., Peters, J.
Proceedings of the 10th European Workshop on Reinforcement Learning, Volume 24
pages: 173, JMLR, European Workshop On Reinforcement Learning, EWRL, 2013 (proceedings)
Schölkopf, B., Luo, Z., Vovk, V.
Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik
Springer, 2013 (book)
2012
Langs, G., Rish, I., Grosse-Wentrup, M., Murphy, B.
Machine Learning and Interpretation in Neuroimaging - Revised Selected and Invited Contributions
pages: 266, Springer, Heidelberg, Germany, International Workshop, MLINI, Held at NIPS, 2012, Lecture Notes in Computer Science, Vol. 7263 (proceedings)
Panagiotaki, E., O’Donnell, L., Schultz, T., Zhang, G.
MICCAI, Workshop on Computational Diffusion MRI, 2012 (electronic publication)
15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Workshop on Computational Diffusion MRI , 2012 (proceedings)
2011
Sra, S., Nowozin, S., Wright, S.
Optimization for Machine Learning
pages: 494, Neural information processing series, MIT Press, Cambridge, MA, USA, December 2011 (book)
Barber, D., Cemgil, A., Chiappa, S.
Bayesian Time Series Models
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)
Kakade, S., von Luxburg, U.
JMLR Workshop and Conference Proceedings Volume 19: COLT 2011
pages: 834, MIT Press, Cambridge, MA, USA, 24th Annual Conference on Learning Theory , June 2011 (proceedings)