Publications

Empirical Inference Conference Paper Learning Hybrid Dynamics and Control Abdulsamad, H., Peters, J. ECML/PKDD 2nd Workshop on Deep Continuous-Discrete Machine Learning, September 2020 (Published) URL BibTeX

Empirical Inference Ph.D. Thesis On the Geometry of Data Representations Bécigneul, G. ETH Zurich, Switzerland, September 2020, (CLS Fellowship Program) (Published) BibTeX

Empirical Inference Conference Paper A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization F Alimisis, F., Orvieto, A., Becigneul, G., Lucchi, A. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:1297-1307, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper A Nonparametric Off-Policy Policy Gradient Tosatto, S., Carvalho, J., Abdulsamad, H., Peters, J. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:167-177, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) BibTeX

Empirical Inference Conference Paper Bayesian Online Prediction of Change Points Agudelo-España, D., Gomez-Gonzalez, S., Bauer, S., Schölkopf, B., Peters, J. Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI), 124:320-329, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Fair Decisions Despite Imperfect Predictions Kilbertus, N., Gomez Rodriguez, M., Schölkopf, B., Muandet, K., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:277-287, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Importance Sampling via Local Sensitivity Raj, A., Musco, C., Mackey, L. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:3099-3109, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Integrals over Gaussians under Linear Domain Constraints Gessner, A., Kanjilal, O., Hennig, P. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:2764-2774, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Kernel Conditional Moment Test via Maximum Moment Restriction Muandet, K., Jitkrittum, W., Kübler, J. M. Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI), 124:41-50, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Model-Agnostic Counterfactual Explanations for Consequential Decisions Karimi, A., Barthe, G., Balle, B., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:895-905, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Modular Block-diagonal Curvature Approximations for Feedforward Architectures Dangel, F., Harmeling, S., Hennig, P. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:799-808, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper More Powerful Selective Kernel Tests for Feature Selection Lim, J. N., Yamada, M., Jitkrittum, W., Terada, Y., Matsui, S., Shimodaira, H. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:820-830, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper On the design of consequential ranking algorithms Tabibian, B., Gómez, V., De, A., Schölkopf, B., Gomez Rodriguez, M. Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI), 124:171-180, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Semi-supervised learning, causality, and the conditional cluster assumption von Kügelgen, J., Mey, A., Loog, M., Schölkopf, B. Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI) , 124:1-10, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020, *also at NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Testing Goodness of Fit of Conditional Density Models with Kernels Jitkrittum, W., Kanagawa, H., Schölkopf, B. Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI), 124:221-230, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Conference Paper A simpler approach to accelerated optimization: iterative averaging meets optimism Joulani, P., Raj, A., Gyoergy, A., Szepesvari, C. Proceedings of the 37th International Conference on Machine Learning, 119:4984-4993, PMLR, Internet, 37th International Conference on Machine Learning, July 2020 (Published) DOI URL BibTeX

Empirical Inference Conference Paper A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming Zhu, J., Muandet, K., Diehl, M., Schölkopf, B. 21st IFAC World Congress, 53(2):7240-7247, July 2020 (Published) arXiv DOI BibTeX

Empirical Inference Ph.D. Thesis Advances in Latent Variable and Causal Models Rubenstein, P. University of Cambridge, UK, July 2020, (Cambridge-Tuebingen-Fellowship) (Published) BibTeX

Empirical Inference Conference Paper Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Kristiadi, A., Hein, M., Hennig, P. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:5436-5446, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Constant Curvature Graph Convolutional Networks Bachmann*, G., Becigneul*, G., Ganea, O. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:486-496, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020, *equal contribution (Published) URL BibTeX

Empirical Inference Ph.D. Thesis Converting to Optimization in Machine Learning: Perturb-and-MAP, Differential Privacy, and Program Synthesis Balog, M. University of Cambridge, UK, July 2020, (Cambridge-Tübingen-Fellowship) (Published) BibTeX

Empirical Inference Conference Paper Differentiable Likelihoods for Fast Inversion of ‘Likelihood-Free’ Dynamical Systems Kersting, H., Krämer, N., Schiegg, M., Daniel, C., Tiemann, M., Hennig, P. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:5154-5164, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), Curran Associates, Inc., Red Hook, NY, Titel 37th International Conference on Machine Learning (ICML 2020), July 2020 (Published) URL BibTeX

Empirical Inference Autonomous Learning Conference Paper Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Hybrid Model Predictive Control Zhu, J., Martius, G. IFAC-PapersOnLine, 21rst IFAC World Congress, 53(2):5239-5245, Elsevier, Amsterdam, 21rst IFAC World Congress, July 2020 (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper Generalized Mean Estimation in Monte-Carlo Tree Search Dam, T., Klink, P., D’Eramo, C., Peters, J., Pajarinen, J. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), 2397-2404, (Editors: Christian Bessiere), International Joint Conferences on Artificial Intelligence Organization, July 2020, Main track (Published) DOI URL BibTeX

Empirical Inference Ph.D. Thesis Learning from Multi-Frame Data Wieschollek, P. University of Tübingen, Germany, July 2020 (Published) BibTeX

Empirical Inference Conference Paper Mixed-Variable Bayesian Optimization Daxberger, E., Makarova, A., Turchetta, M., Krause, A. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20, 2633-2639, (Editors: Christian Bessiere), International Joint Conferences on Artificial Intelligence Organization, July 2020 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization Negiar, G., Dresdner, G., Tsai, A. Y., El Ghaoui, L., Locatello, F., Freund, R. M., Pedregosa, F. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:7253-7262, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Variational Autoencoders with Riemannian Brownian Motion Priors Kalatzis, D., Eklund, D., Arvanitidis, G., Hauberg, S. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:5053-5066, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Variational Bayes in Private Settings (VIPS) (Extended Abstract) Foulds, J. R., Park, M., Chaudhuri, K., Welling, M. Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), 5050-5054, (Editors: Christian Bessiere), International Joint Conferences on Artificial Intelligence Organization, July 2020, Journal track (Published) DOI URL BibTeX

Empirical Inference Conference Paper Weakly-Supervised Disentanglement Without Compromises Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., Tschannen, M. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:6348-6359, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX

Empirical Inference Conference Paper A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control Zhu, J., Diehl, M., Schölkopf, B. 2nd Annual Conference on Learning for Dynamics and Control (L4DC), 120:915-923, Proceedings of Machine Learning Research, (Editors: Alexandre M. Bayen and Ali Jadbabaie and George Pappas and Pablo A. Parrilo and Benjamin Recht and Claire Tomlin and Melanie Zeilinger), PMLR, June 2020 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data Rawal*, R., Pradhan*, P. In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020), 350-359, IEEE, Piscataway, NJ, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020), June 2020, *equal contribution (Published) DOI URL BibTeX

Empirical Inference Conference Paper Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation Abdulsamad, H., Peters, J. Proceedings of the 2nd Conference on Learning for Dynamics and Control (L4DC), 120:904-914, Proceedings of Machine Learning Research, (Editors: Alexandre M. Bayen and Ali Jadbabaie and George Pappas and Pablo A. Parrilo and Benjamin Recht and Claire Tomlin and Melanie Zeilinger), PMLR, June 2020 URL BibTeX

Empirical Inference Conference Paper Kernel Conditional Density Operators Schuster, I., Mollenhauer, M., Klus, S., Muandet, K. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:993-1004, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, June 2020 (Published) URL BibTeX

Empirical Inference Article Phenomenal Causality and Sensory Realism Meding, K., Bruijns, S. A., Schölkopf, B., Berens, P., Wichmann, F. A. i-Perception, 11(3):1-16, June 2020 (Published) DOI URL BibTeX

Empirical Inference Master Thesis Deep learning for the parameter estimation of tight-binding Hamiltonians Cacioppo, A. University of Roma, La Sapienza, Italy, May 2020 (Published) BibTeX

Empirical Inference Article Variational Bayes In Private Settings (VIPS) Park, M., Foulds, J., Chaudhuri, K., Welling, M. Journal of Artificial Intelligence Research, 68:109-157, May 2020 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Towards Robot Skill Learning Peters, J. Proceedings 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 3-3, IEEE, April 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper A meta-transfer objective for learning to disentangle causal mechanisms Bengio, Y., Deleu, T., Rahaman, N., Ke, R., Lachapelle, S., Bilaniuk, O., Goyal, A., Pal, C. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) arXiv URL BibTeX

Dynamic Locomotion Movement Generation and Control Autonomous Motion Empirical Inference Robotics Article An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research Grimminger, F., Meduri, A., Khadiv, M., Viereck, J., Wüthrich, M., Naveau, M., Berenz, V., Heim, S., Widmaier, F., Flayols, T., et al. IEEE Robotics and Automation Letters, 5(2):3650-3657, IEEE, April 2020 (Published) Youtube Open Dynamic Robot Initiative DOI URL BibTeX

Empirical Inference Conference Paper BackPACK: Packing more into Backprop Dangel, F., Kunstner, F., Hennig, P. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Counterfactuals uncover the modular structure of deep generative models Besserve, M., Mehrjou, A., Sun, R., Schölkopf, B. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Disentangling Factors of Variations Using Few Labels Locatello, F., Tschannen, M., Bauer, S., Rätsch, G., Schölkopf, B., Bachem, O. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) arXiv URL BibTeX

Empirical Inference Perceiving Systems Probabilistic Learning Group Conference Paper From Variational to Deterministic Autoencoders Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B. 8th International Conference on Learning Representations (ICLR) , April 2020, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Master Thesis Learning Algorithms, Invariances, and the Real World Zecevic, M. Technical University of Darmstadt, Germany, April 2020 (Published) BibTeX

Empirical Inference Conference Paper Learning the Arrow of Time for Problems in Reinforcement Learning Rahaman, N., Wolf, S., Goyal, A., Remme, R., Bengio, Y. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Mixed-curvature Variational Autoencoders Skopek, O., Ganea, O., Becigneul, G. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals Laumann, F., von Kügelgen, J., Barahona, M. ICLR 2020 Workshop "Tackling Climate Change with Machine Learning", April 2020 (Published) arXiv PDF BibTeX

Empirical Inference Conference Paper On Mutual Information Maximization for Representation Learning Tschannen, M., Djolonga, J., Rubenstein, P. K., Gelly, S., Lucic, M. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) arXiv URL BibTeX

Empirical Inference Perceiving Systems Article Real Time Trajectory Prediction Using Deep Conditional Generative Models Gomez-Gonzalez, S., Prokudin, S., Schölkopf, B., Peters, J. IEEE Robotics and Automation Letters, 5(2):970-976, IEEE, April 2020 (Published) arXiv DOI BibTeX

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