Publications

Empirical Inference Conference Paper A Class of Algorithms for General Instrumental Variable Models Kilbertus, N., Kusner, M. J., Silva, R. Advances of Neural Information Processing Systems 33 (NeurIPS 2020), 33:20108-20119, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates Inc., 34th Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings Park, J., Muandet, K. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :21247-21259, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Karimi*, A., von Kügelgen*, J., Schölkopf, B., Valera, I. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :265-277, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Barking up the right tree: an approach to search over molecule synthesis DAGs Bradshaw, J., Paige, B., Kusner, M., Segler, M., Hernández-Lobato, J. M. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :6852-6866, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Ph.D. Thesis Causal Feature Selection in Neuroscience Mastakouri, A. University of Tübingen, Germany, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Causal analysis of Covid-19 Spread in Germany Mastakouri, A., Schölkopf, B. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :3153-3163, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Dual Instrumental Variable Regression Muandet, K., Mehrjou, A., Lee, S. K., Raj, A. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :2710-2721, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Learning Kernel Tests Without Data Splitting Kübler, J. M., Jitkrittum, W., Schölkopf, B., Muandet, K. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :6245-6255, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Modeling Shared responses in Neuroimaging Studies through MultiView ICA Richard, H., Gresele, L., Hyvärinen, A., Thirion, B., Gramfort, A., Ablin, P. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :19149-19162, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., Red Hook, NY, 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Object-Centric Learning with Slot Attention Locatello, F., Weissenborn, D., Unterthiner, T., Mahendran, A., Heigold, G., Uszkoreit, J., Dosovitskiy, A., Kipf, T. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :11525-11538, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Probabilistic Linear Solvers for Machine Learning Wenger, J., Hennig, P. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :6731-6742, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Relative gradient optimization of the Jacobian term in unsupervised deep learning Gresele, L., Fissore, G., Javaloy, A., Schölkopf, B., Hyvarinen, A. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :16567-16578, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining Tripp, A., Daxberger, E., Hernández-Lobato, J. M. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :11259-11272, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Self-Paced Deep Reinforcement Learning Klink, P., D’Eramo, C., Peters, J., Pajarinen, J. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :9216-9227, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Stochastic Stein Discrepancies Gorham, J., Raj, A., Mackey, L. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :17931-17942, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem Zhu, J., Jitkrittum, W., Diehl, M., Schölkopf, B. In 59th IEEE Conference on Decision and Control (CDC), :3457-3463, IEEE, December 2020 (Published) arXiv DOI BibTeX

Empirical Inference Conference Paper MATE: Plugging in Model Awareness to Task Embedding for Meta Learning Chen, X., Wang, Z., Tang, S., Muandet, K. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), :11865-11877, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning Shaj, V., Becker, P., Büchler, D., Pandya, H., van Duijkeren, N., Taylor, C. J., Hanheide, M., Neumann, G. Proceedings of the 4th Conference on Robot Learning (CoRL), 155:765-781, Proceedings of Machine Learning Research, (Editors: Jens Kober and Fabio Ramos and Claire J. Tomlin), PMLR, November 2020 (Published) PDF URL BibTeX

Empirical Inference Conference Paper Advances in Human-Robot Handshaking Prasad, V., Stock-Homburg, R., Peters, J. Social Robotics - 12th International Conference (ICSR), 12483:478-489, Lecture Notes in Computer Science, (Editors: Wager, A. R. and Feil-Seifer, D. and Haring, K. S. and Rossi, S. and Willians, T. and He, H. and Sam Ge, S.), Springer, November 2020 (Published) DOI BibTeX

Empirical Inference Ph.D. Thesis Enforcing and Discovering Structure in Machine Learning Locatello, F. ETH Zurich, Switzerland, November 2020, (CLS Fellowship Program) (Published) BibTeX

Perceiving Systems Empirical Inference Conference Paper Grasping Field: Learning Implicit Representations for Human Grasps Karunratanakul, K., Yang, J., Zhang, Y., Black, M., Muandet, K., Tang, S. In 2020 International Conference on 3D Vision (3DV 2020), :333-344, IEEE, Piscataway, NJ, International Conference on 3D Vision (3DV 2020), November 2020 (Published) pdf arXiv code DOI BibTeX

Empirical Inference Conference Paper High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards Ploeger, K., Lutter, M., Peters, J. Proceedings of the 4th Conference on Robot Learning (CoRL), 155:642-653, Proceedings of Machine Learning Research, (Editors: Jens Kober and Fabio Ramos and Claire J. Tomlin), PMLR, November 2020 (Published) URL BibTeX

Empirical Inference Conference Paper Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis Xing, X., Jin, Z., Jin, D., Wang, B., Zhang, Q., Huang, X. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), :3594-3605, (Editors: Bonnie Webber, Trevor Cohn, Yulan He, and Yang Liu), Association for Computational Linguistics, Online, November 2020 (Published) PDF DOI URL BibTeX

Empirical Inference Autonomous Motion Movement Generation and Control Conference Paper TriFinger: An Open-Source Robot for Learning Dexterity Wüthrich, M., Widmaier, F., Grimminger, F., Akpo, J., Joshi, S., Agrawal, V., Hammoud, B., Khadiv, M., Bogdanovic, M., Berenz, V., et al. Proceedings of the 4th Conference on Robot Learning (CoRL), 155:1871-1882, Proceedings of Machine Learning Research, (Editors: Jens Kober and Fabio Ramos and Claire J. Tomlin), PMLR, November 2020 (Published) PDF URL BibTeX

Empirical Inference Master Thesis A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging DuMont Schütte, A. ETH Zurich, Switzerland, October 2020 (Published) BibTeX

Empirical Inference Master Thesis A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ahmed, O. ETH Zurich, Switzerland, October 2020 (Published) BibTeX

Empirical Inference Article Exploring the Relationship Between EMG Feature Space Characteristics and Control Performance in Machine Learning Myoelectric Control Franzke, A. W., Kristoffersen, M. B., Jayaram, V., Sluis, C. K. V. D., Murgia, A., Bongers, R. M. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29:21-30, IEEE, October 2020 (Published) DOI BibTeX

Empirical Inference Article Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort Studies Küstner, T., Hepp, T., Fischer, M., Schwartz, M., Fritsche, A., Häring, H., Nikolaou, K., Bamberg, F., Yang, B., Schick, F., et al. Radiology: Artificial Intelligence, 2(6), October 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware Hohmann, M. R., Konieczny, L., Hackl, M., Wirth, B., Zaman, T., Enficiaud, R., Grosse-Wentrup, M., Schölkopf, B. Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (UIST), :1071-1084, Association for Computing Machinery, October 2020 (Published) arXiv DOI BibTeX

Empirical Inference Ph.D. Thesis Beyond traditional assumptions in fair machine learning Kilbertus, N. University of Cambridge, UK, September 2020, (Cambridge-Tübingen-Fellowship) (Published) BibTeX

Empirical Inference Conference Paper Detection of diabetes from whole-body magnetic resonance imaging using deep learning Wagner, R., Dietz, B., Machann, J., Schwab, P., Dienes, J., Reichert, S., Birkenfeld, A. L., Haering, H., Schick, F., Stefan, N., et al. Diabetologia - 56th EASD Annual Meeting of the European Association for the Study of Diabetes, 63(1-supplement):551, September 2020 (Published) Poster URL BibTeX

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

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