Publications

Empirical Inference Conference Paper Neighborhood Contrastive Learning Applied to Online Patient Monitoring Yèche, H., Dresdner, G., Locatello, F., Hüser, M., Rätsch, G. Proceedings of 38th International Conference on Machine Learning, 139:11964-11974, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, The 38th International Conference on Machine Learning (ICML 2021), July 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Neural Symbolic Regression that Scales Biggio*, L., Bendinelli*, T., Neitz, A., Lucchi, A., Parascandolo, G. Proceedings of 38th International Conference on Machine Learning (ICML 2021), 139:936-945, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, The 38th International Conference on Machine Learning (ICML 2021), July 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper On Disentangled Representations Learned From Correlated Data Träuble, F., Creager, E., Kilbertus, N., Locatello, F., Dittadi, A., Goyal, A., Schölkopf, B., Bauer, S. Proceedings of 38th International Conference on Machine Learning (ICML), 139:10401-10412, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, July 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction Mastouri, A., Zhu, Y., Gultchin, L., Korba, A., Silva, R., Kusner, M., Gretton, A., Muandet, K. Proceedings of 38th International Conference on Machine Learning (ICML), 139:7512-7523, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, July 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Representation Learning for Out-of-distribution Generalization in Reinforcement Learning Learning Träuble*, F., Dittadi*, A., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., Locatello, F., Bachem, O., Schölkopf, B., Bauer, S. ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , July 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Robust Value Iteration for Continuous Control Tasks Lutter, M., Mannor, S., Peters, J., Fox, D., Garg, A. Robotics: Science and Systems XVII (R:SS 2021), (Editors: Dylan A. Shell and Marc Toussaint and M. Ani Hsieh), July 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Immer, A., Bauer, M., Fortuin, V., Rätsch, G., Khan, M. E. Proceedings of 38th International Conference on Machine Learning (ICML), 139:4563-4573, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, July 2021 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Value Iteration in Continuous Actions, States and Time Lutter, M., Mannor, S., Peters, J., Fox, D., Garg, A. Proceedings of 38th International Conference on Machine Learning (ICML), 139:7224-7234, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, July 2021 (Published) URL BibTeX

Empirical Inference Article SKID RAW: Skill Discovery From Raw Trajectories Tanneberg, D., Ploeger, K., Rueckert, E., Peters, J. IEEE Robotics and Automation Letters, 6(3):4696-4703, IEEE, New York, NY, July 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach Nemmour, Y., Schölkopf, B., Zhu, J. Proceedings of the 3rd Conference on Learning for Dynamics and Control (L4DC), 144:1255-1269, Proceedings of Machine Learning Research, (Editors: Jadbabaie, Ali and Lygeros, John and Pappas, George J. and Parrilo, Pablo A. and Recht, Benjamin and Tomlin, Claire J. and Zeilinger, Melanie N.), PMLR, June 2021 (Published) URL BibTeX

Empirical Inference Article Automated Morphometric Analysis of the Hip Joint on MRI from the German National Cohort Study Fischer, M., Walter, S. S., Hepp, T., Zimmer, M., Notohamiprodjo, M., Schick, F., Yang, B. Radiology: Artificial Intelligence, 3(5), June 2021 (Published) DOI BibTeX

Empirical Inference Ph.D. Thesis Causal Inference in Vision Meding, K. Eberhard Karls Universität Tübingen, Tübingen, June 2021 (Published) BibTeX

Empirical Inference Article Deep Learning-Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies Kart, T., Fischer, M., Küstner, T., Hepp, T., Bamberg, F., Winzeck, S., Glocker, B., Rueckert, D., Gatidis, S. Investigative Radiology, 56(6):401-408, June 2021 (Published) DOI BibTeX

Empirical Inference Article Discrimination of simple objects decoded from the output of retinal ganglion cells upon sinusoidal electrical stimulation Corna, A., Ramesh, P., Jetter, F., Lee, M., Macke, J. H., Zeck, G. Journal of Neural Engineering, 18(4), June 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper Distilling Audio-Visual Knowledge by Compositional Contrastive Learning Chen, Y., Xian, Y., Koepke, A. S., Akata, Z. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), :7016-7025, Computer Vision Foundation / IEEE, CVPR, June 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Learning Decision Trees Recurrently Through Communication Alaniz, S., Marcos, D., Schiele, B., Akata, Z. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), :13518-13527, Computer Vision Foundation / IEEE, CVPR, June 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Learning Graph Embeddings for Compositional Zero-shot Learning Naeem, M. F., Xian, Y., Tombari, F., Akata, Z. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), :953-962, Computer Vision Foundation / IEEE, CVPR, June 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Neural Lyapunov Redesign Mehrjou, A., Ghavamzadeh, M., Schölkopf, B. Proceedings of the 3rd Conference on Learning for Dynamics and Control (L4DC), 144:459-470, Proceedings of Machine Learning Research, (Editors: Jadbabaie, Ali and Lygeros, John and Pappas, George J. and Parrilo, Pablo A. and Recht, Benjamin and Tomlin, Claire J. and Zeilinger, Melanie N.), PMLR, 3rd Annual Conference on Learning for Dynamics and Control (L4DC) , June 2021 (Published) URL BibTeX

Empirical Inference Ph.D. Thesis Optimization Algorithms for Machine Learning Raj, A. University of Tübingen, Germany, June 2021 (Published) BibTeX

Empirical Inference Conference Paper Orthogonal Over-Parameterized Training Liu, W., Lin, R., Liu, Z., Rehg, J., Paull, L., Xiong, L., Song, L., Weller, A. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), :7251-7260, Computer Vision Foundation / IEEE, CVPR, June 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Uncertainty-Based Biological Age Estimation of Brain MRI Scans Armanious, K., Abdulatif, S., Shi, W., Hepp, T., Gatidis, S., Yang, B. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), :1100-1104, IEEE, June 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ahmed*, O., Träuble*, F., Goyal, A., Neitz, A., Bengio, Y., Schölkopf, B., Wüthrich, M., Bauer, S. In 9th International Conference on Learning Representations (ICLR 2021), :20, ICLR, Wien, International Conference on Learning Representations (ICLR), May 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper A teacher-student framework to distill future trajectories Neitz*, A., Parascandolo*, G., Schölkopf, B. In 9th International Conference on Learning Representations (ICLR), May 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Fast And Slow Learning Of Recurrent Independent Mechanisms Madan, K., Ke, N. R., Goyal, A., Schölkopf, B., Bengio, Y. In 9th International Conference on Learning Representations (ICLR), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Learning explanations that are hard to vary Parascandolo*, G., Neitz*, A., Orvieto, A., Gresele, L., Schölkopf, B. In 9th International Conference on Learning Representations (ICLR), May 2021, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Predicting Infectiousness for Proactive Contact Tracing Bengio, Y., Gupta, P., Maharaj, T., Rahaman, N., Weiss, M., Deleu, T., Muller, E. B., Qu, M., Schmidt, V., St-Charles, P., et al. In The Ninth International Conference on Learning Representations (ICLR 2021), 9th International Conference on Learning Representations (ICLR), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator Paulus, M. B., Maddison, C. J., Krause, A. In The Ninth International Conference on Learning Representations , 9th International Conference on Learning Representations (ICLR 2021), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Spatially Structured Recurrent Modules Rahaman, N., Goyal, A., Gondal, M. W., Wüthrich, M., Bauer, S., Sharma, Y., Bengio, Y., Schölkopf, B. In 9th International Conference on Learning Representations (ICLR), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk Watson, J., Peters, J. American Control Conference (ACC), :1231-1236, IEEE, ACC, May 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills Tosatto, S., Chalvatzaki, G., Peters, J. 2021 IEEE International Conference on Robotics and Automation (ICRA), :10815-10821, IEEE, IEEE International Conference on Robotics and Automation (ICRA 2021) , May 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning Lutter, M., Silberbauer, J., Watson, J., Peters, J. IEEE International Conference on Robotics and Automation (ICRA), :4163-4170, IEEE, May 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Directed Acyclic Graph Neural Network for Human Motion Prediction Li, Q., Chalvatzaki, G., Peters, J., Wang, Y. 2021 IEEE International Conference on Robotics and Automation (ICRA), :3197-3204, IEEE, IEEE International Conference on Robotics and Automation (ICRA 2021), May 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Learning Human-like Hand Reaching for Human-Robot Handshaking Prasad, V., Stock-Homburg, R., Peters, J. 2021 IEEE International Conference on Robotics and Automation (ICRA), :3612-3618, IEEE, IEEE International Conference on Robotics and Automation (ICRA 2021), May 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Meta Attention Networks: Meta-Learning Attention to Modulate Information Between Recurrent Independent Mechanisms Madan, K., Ke, N. R., Goyal, A., Schölkopf, B., Bengio, Y. 9th International Conference on Learning Representations (ICLR), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning Morgan, A., Nandha, D., Chalvatzaki, G., D’Eramo, C., Dollar, A., Peters, J. IEEE International Conference on Robotics and Automation (ICRA), :6672-6678, IEEE, May 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper On the Transfer of Disentangled Representations in Realistic Settings Dittadi*, A., Träuble*, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther, O., Bauer, S., Schölkopf, B. In The Ninth International Conference on Learning Representations (ICLR), The 9th International Conference on Learning Representations (ICLR 2021) , May 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Recurrent Independent Mechanisms Goyal, A., Lamb, A., Hoffmann, J., Sodhani, S., Levine, S., Bengio, Y., Schölkopf, B. In The Ninth International Conference on Learning Representations (ICLR), 9th International Conference on Learning Representations (ICLR 2021), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper ResNet After All: Neural ODEs and Their Numerical Solution Ott, K., Katiyar, P., Hennig, P., Tiemann, M. In The Ninth International Conference on Learning Representations (ICLR 2021), 9th International Conference on Learning Representations (ICLR), May 2021 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Scaling Guarantees for Nearest Counterfactual Explanations Mohammadi, K., Karimi, A., Barthe, G., Valera, I. AIES ’21: Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, :177-187, (Editors: Marion Fourcade, Benjamin Kuipers, Seth Lazar and Deirdre K. Mulligan), ACM, New York, NY, Fourth AAAI/ACM Conference on AI, Ethics, and Society (AIES 2021), May 2021 (Published) arXiv DOI BibTeX

Empirical Inference Conference Paper Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling Miladinović, D., Stanić, A., Bauer, S., Schmidhuber, J., Buhmann, J. M. In The 9th International Conference on Learning Representations (ICLR), The Ninth International Conference on Learning Representations (ICLR 2021), May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Visual Representation Learning Does Not Generalize Strongly Within the Same Domain Schott, L., von Kügelgen, J., Träuble, F., Gehler, P., Russell, C., Bethge, M., Schölkopf, B., Locatello, F., Brendel, W. ICLR 2021 - Workshop on Generalization beyond the training distribution in brains and machines, May 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Benchmarking Simulation-Based Inference Lueckmann, J., Boelts, J., Greenberg, D. S., Gonçalves, P. J., Macke, J. H. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:343-351, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Calibrated Adaptive Probabilistic ODE Solvers Bosch, N., Hennig, P., Tronarp, F. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:3466-3474, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Conference Paper DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation Harder, F., Adamczewski, K., Park, M. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:1819-1827, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Article Data-efficient Domain Randomization with Bayesian Optimization Muratore, F., Eilers, C., Gienger, M., Peters, J. IEEE Robotics and Automation Letters , 6(2):911-918, April 2021 (Published) DOI BibTeX

Empirical Inference Conference Paper Dirichlet pruning for neural network compression Adamczewski, K., Park, M. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:3637-3645, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Explicit Regularization of Stochastic Gradient Methods through Duality Raj, A., Bach, F. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:1882-1890, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings Guo, Q., Jin, Z., Wang, Z., Qiu, X., Zhang, W., Zhu, J., Zhang, Z., Wipf, D. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:1828-1836, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Geometrically Enriched Latent Spaces Arvanitidis, G., Hauberg, S., Schölkopf, B. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:631-639, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, AISTATS, April 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation Zhu, J., Jitkrittum, W., Diehl, M., Schölkopf, B. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:280-288, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, April 2021 (Published) arXiv URL BibTeX

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