Publications

Empirical Inference Conference Paper Stochastic Optimal Control as Approximate Input Inference Watson, J., Abdulsamad, H., Peters, J. Proceedings of the 3rd Annual Conference on Robot Learning (CoRL), 100:697-716, Proceedings of Machine Learning Research, (Editors: Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura), PMLR, November 2019 (Published) URL BibTeX

Empirical Inference Conference Paper HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints Lutter, M., Belousov, B., Listmann, K., Clever, D., Peters, J. Proceedings of the 3rd Annual Conference on Robot Learning (CoRL), 100:640-650, Proceedings of Machine Learning Research, (Editors: Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura), PMLR, November 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Building a Library of Tactile Skills Based on FingerVision Belousov, B., Sadybakasov, A., Wibranek, B., Veiga, F., Tessmann, O., Peters, J. International Conference on Humanoid Robots (Humanoids), :717-722, IEEE, October 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Neural Signatures of Motor Skill in the Resting Brain Ozdenizci, O., Meyer, T., Wichmann, F., Peters, J., Schölkopf, B., Cetin, M., Grosse-Wentrup, M. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC 2019), :4387-4394, IEEE, October 2019 (Published) DOI BibTeX

Empirical Inference Master Thesis Inferring the Band Structure from Band Mapping Data through Machine Learning Stimper, V. Technical University of Munich, September 2019 (Published) BibTeX

Empirical Inference Conference Paper A Differentially Private Kernel Two-Sample Test Raj*, A., Law*, L., Sejdinovic*, D., Park, M. Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 119066:697-724, Lecture Notes in Computer Science, (Editors: Brefeld, Ulf and Fromont, Elisa and Hotho, Andreas and Knobbe, Arno and Maathuis, Marloes and Robardet, Céline), Springer International Publishing, September 2019, *equal contribution (Published) DOI BibTeX

Empirical Inference Article Color Constancy in Deep Neural Networks Flachot, A., Schuett, H., Fleming, R. W., Wichmann, F. A., Gegenfurtner, K. R. Journal of Vision, 19(10):article no. 298, September 2019 (Published) DOI BibTeX

Empirical Inference Article Convolutional neural networks: A magic bullet for gravitational-wave detection? Gebhard, T., Kilbertus, N., Harry, I., Schölkopf, B. Physical Review D, 100(6):article no. 063015, American Physical Society, September 2019 (Published) DOI URL BibTeX

Empirical Inference Article Data scarcity, robustness and extreme multi-label classification Babbar, R., Schölkopf, B. Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (Published) DOI BibTeX

Empirical Inference Master Thesis Learning to Diagnose Diabetes from Magnetic Resonance Tomography Dietz, B. ETH Zurich, Switzerland, August 2019 (Published) BibTeX

Empirical Inference Bachelor Thesis Automatic Segmentation and Labelling for Robot Table Tennis Time Series Lutz, P. Technical University Darmstadt, Germany, August 2019 (Published) BibTeX

Empirical Inference Poster Perception of temporal dependencies in autoregressive motion Meding, K., Schölkopf, B., Wichmann, F. A. Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (Published) URL BibTeX

Empirical Inference Poster Phenomenal Causality and Sensory Realism Bruijns, S. A., Meding, K., Schölkopf, B., Wichmann, F. A. Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Assessing Transferability in Reinforcement Learning from Randomized Simulations Muratore, F., Gienger, M., Peters, J. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), July 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Belief space model predictive control for approximately optimal system identification Belousov, B., Abdulsamad, H., Schultheis, M., Peters, J. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), July 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Beta Power May Mediate the Effect of Gamma-TACS on Motor Performance Mastakouri, A., Schölkopf, B., Grosse-Wentrup, M. 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), :5902-5908, July 2019 (Published) arXiv PDF DOI URL BibTeX

Empirical Inference Conference Paper Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory Geiger, P., Besserve, M., Winkelmann, J., Proissl, C., Schölkopf, B. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 115:207-216, Proceedings of Machine Learning Research, (Editors: Adams, Ryan P. and Gogate, Vibhav), PMLR, July 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Deep Optimal Control: Using the Euler-Lagrange Equation to learn an Optimal Feedback Control Law Lutter, M., Peters, J. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), July 2019 () URL BibTeX

Empirical Inference Conference Paper Exploration Driven by an Optimistic Bellman Equation Tosatto, S., D’Eramo, C., Pajarinen, J., Restelli, M., Peters, J. International Joint Conference on Neural Networks (IJCNN), :1-8, July 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Measuring Similarities between Markov Decision Processes Klink, P., Peters, J. 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), July 2019 (Published) URL BibTeX

Empirical Inference Poster Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation Shao, K., Logothetis, N., Besserve, M. 28th Annual Computational Neuroscience Meeting (CNS*2019), July 2019 (Published) DOI BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning Peharz, R., Vergari, A., Stelzner, K., Molina, A., Shao, X., Trapp, M., Kersting, K., Ghahramani, Z. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 115:334-344, Proceedings of Machine Learning Research, (Editors: Adams, Ryan P. and Gogate, Vibhav), PMLR, July 2019 (Published) URL BibTeX

Empirical Inference Master Thesis Reinforcement Learning for a Two-Robot Table Tennis Simulation Li, G. RWTH Aachen University, Germany, July 2019 (Published) BibTeX

Empirical Inference Conference Paper The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA Gresele*, L., Rubenstein*, P. K., Mehrjou, A., Locatello, F., Schölkopf, B. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 115:217-227, Proceedings of Machine Learning Research, (Editors: Adams, Ryan P. and Gogate, Vibhav), PMLR, July 2019, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper The Sensitivity of Counterfactual Fairness to Unmeasured Confounding Kilbertus, N., Ball, P. J., Kusner, M. J., Weller, A., Silva, R. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 115:616-626, Proceedings of Machine Learning Research, (Editors: Adams, Ryan P. and Gogate, Vibhav), PMLR, July 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities Ganea, O., Gelly, S., Becigneul, G., Severyn, A. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:2073-2082, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Locatello, F., Bauer, S., Lucic, M., Raetsch, G., Gelly, S., Schölkopf, B., Bachem, O. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:4114-4124, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper First-Order Adversarial Vulnerability of Neural Networks and Input Dimension Simon-Gabriel, C., Ollivier, Y., Bottou, L., Schölkopf, B., Lopez-Paz, D. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:5809-5817, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Generate Semantically Similar Images with Kernel Mean Matching Jitkrittum*, W., Sangkloy*, P., Gondal, M. W., Raj, A., Hays, J., Schölkopf, B. 6th Workshop Women in Computer Vision (WiCV) (oral presentation), June 2019, *equal contribution (Published) BibTeX

Empirical Inference Conference Paper Kernel Mean Matching for Content Addressability of GANs Jitkrittum*, W., Sangkloy*, P., Gondal, M. W., Raj, A., Hays, J., Schölkopf, B. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:3140-3151, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019, *equal contribution (Published) PDF URL BibTeX

Perceiving Systems Empirical Inference Conference Paper Local Temporal Bilinear Pooling for Fine-grained Action Parsing Zhang, Y., Tang, S., Muandet, K., Jarvers, C., Neumann, H. In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), :12005-12015, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2019 () Code video demo pdf URL BibTeX

Empirical Inference Conference Paper Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models Ialongo, A. D., Van Der Wilk, M., Hensman, J., Rasmussen, C. E. In Proceedings of the 36th International Conference on Machine Learning (ICML), 97:2931-2940, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Projections for Approximate Policy Iteration Algorithms Akrour, R., Pajarinen, J., Peters, J., Neumann, G. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:181-190, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Suter, R., Miladinovic, D., Schölkopf, B., Bauer, S. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:6056-6065, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Switching Linear Dynamics for Variational Bayes Filtering Becker-Ehmck, P., Peters, J., van der Smagt, P. Proceedings of the 36th International Conference on Machine Learning (ICML), 97:553-562, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning Lutter, M., Ritter, C., Peters, J. 7th International Conference on Learning Representations (ICLR), ICLR, 7th International Conference on Learning Representations (ICLR), May 2019 (Published) URL BibTeX

Probabilistic Numerics Empirical Inference Conference Paper DeepOBS: A Deep Learning Optimizer Benchmark Suite Schneider, F., Balles, L., Hennig, P. 7th International Conference on Learning Representations (ICLR), May 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Meta-Learning Probabilistic Inference for Prediction Gordon, J., Bronskill, J., Bauer, M., Nowozin, S., Turner, R. 7th International Conference on Learning Representations (ICLR), ICLR, 7th International Conference on Learning Representations (ICLR), May 2019 (Published) URL BibTeX

Empirical Inference Conference Paper SOM-VAE: Interpretable Discrete Representation Learning on Time Series Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., Rätsch, G. 7th International Conference on Learning Representations (ICLR), ICLR, 7th International Conference on Learning Representations (ICLR), May 2019 (Published) URL BibTeX

Empirical Inference Master Thesis Characteristics of longitudinal physiological measurements of late-stage ALS patients Konieczny, L. Ludwig-Maximilians-Universität München, Germany, May 2019 (Published) BibTeX

Empirical Inference Conference Paper Disentangled State Space Models: Unsupervised Learning of Dynamics across Heterogeneous Environments Miladinović*, D., Gondal*, M. W., Schölkopf, B., Buhmann, J. M., Bauer, S. Deep Generative Models for Highly Structured Data Workshop at ICLR, May 2019, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Foundations and New Horizons for Causal Inference Meinshausen, N., Peters, J., Richardson, T. S., Schölkopf, B. In Oberwolfach Reports, 16(2):1499-1571, May 2019 (Published) DOI URL BibTeX

Empirical Inference Conference Paper MYND: A Platform for Large-scale Neuroscientific Studies Hohmann, M. R., Hackl, M., Wirth, B., Zaman, T., Enficiaud, R., Grosse-Wentrup, M., Schölkopf, B. Proceedings of the 2019 Conference on Human Factors in Computing Systems (CHI), :1-6, Association for Computing Machinery, May 2019 () DOI BibTeX

Probabilistic Numerics Empirical Inference Conference Paper Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization de Roos, F., Hennig, P. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs Wenk, P., Gotovos, A., Bauer, S., Gorbach, N., Krause, A., Buhmann, J. M. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1351-1360, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF PDF URL BibTeX

Probabilistic Numerics Empirical Inference Conference Paper Fast and Robust Shortest Paths on Manifolds Learned from Data Arvanitidis, G., Hauberg, S., Hennig, P., Schober, M. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Resampled Priors for Variational Autoencoders Bauer, M., Mnih, A. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:66-75, Proceedings of Machine Learning Research, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) arXiv URL BibTeX

Empirical Inference Article SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species Miladinovic, D., Muheim, C., Bauer, S., Spinnler, A., Noain, D., Bandarabadi, M., Gallusser, B., Krummenacher, G., Baumann, C., Adamantidis, A., et al. PLOS Computational Biology, 15(4):article no. e1006968, Public Library of Science, April 2019 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features von Kügelgen, J., Mey, A., Loog, M. In Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1361-1369, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF Poster URL BibTeX

Empirical Inference Conference Paper Sobolev Descent Mroueh, Y., Sercu, T., Raj, A. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:2976-2985, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF URL BibTeX

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