2023
Berenz, V., Widmaier, F., Guist, S., Schölkopf, B., Büchler, D.
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Robot Software Architectures Workshop (RSA) 2023, ICRA, 2023 (techreport)
Bottou, L., Schölkopf, B.
Borges und die Künstliche Intelligenz
2023, published in Frankfurter Allgemeine Zeitung, 18 December 2023, Nr. 294 (misc)
2022
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)
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
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)
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
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)
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
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)
2015
Besserve, M.
Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism
53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)
Besserve, M.
Independence of cause and mechanism in brain networks
DALI workshop on Networks: Processes and Causality, April 2015 (talk)
Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D.
Information-Theoretic Implications of Classical and Quantum Causal Structures
18th Conference on Quantum Information Processing (QIP), 2015 (talk)
Abbott, T., Abdalla, F. B., Allam, S., Amara, A., Annis, J., Armstrong, R., Bacon, D., Banerji, M., Bauer, A. H., Baxter, E., others,
Cosmology from Cosmic Shear with DES Science Verification Data
arXiv preprint arXiv:1507.05552, 2015 (techreport)
Jarvis, M., Sheldon, E., Zuntz, J., Kacprzak, T., Bridle, S. L., Amara, A., Armstrong, R., Becker, M. R., Bernstein, G. M., Bonnett, C., others,
The DES Science Verification Weak Lensing Shear Catalogs
arXiv preprint arXiv:1507.05603, 2015 (techreport)
Foreman-Mackey, D., Hogg, D. W., Schölkopf, B.
The search for single exoplanet transits in the Kepler light curves
IAU General Assembly, 22, pages: 2258352, 2015 (talk)
2014
Kober, J., Peters, J.
Learning Motor Skills: From Algorithms to Robot Experiments
97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)
Besserve, M., Schölkopf, B., Logothetis, N. K.
Unsupervised identification of neural events in local field potentials
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)
Besserve, M.
Quantifying statistical dependency
Research Network on Learning Systems Summer School, 2014 (talk)
Janzing, D.
Causal Inference from Passive Observations
24th Summer School University of Jyväskylā, Finland, August, 2014 (talk)
2013
Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A.
Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)
Mantlik, F., Bezrukov, I., Hofmann, M., Schölkopf, B., Pichler, B.
MR-Based Attenuation Correction for Combined Brain PET/MR: Robustness of Atlas- and Pattern Recognition Method to Atlas Registration Failures
IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE MIC), 2013 (talk)
Hennig, P.
Animating Samples from Gaussian Distributions
(8), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2013 (techreport)
Muandet, K.
Domain Generalization via Invariant Feature Representation
30th International Conference on Machine Learning (ICML2013), 2013 (talk)