Publications

Empirical Inference Conference Paper A Witness Two-Sample Test Kübler, J. M., Jitkrittum, W., Schölkopf, B., Muandet, K. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:1403-1419, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper A prior-based approximate latent Riemannian metric Arvanitidis, G., Georgiev, B., Schölkopf, B. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:4634-4658, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Adversarially Robust Kernel Smoothing Zhu, J., Kouridi, C., Nemmour, Y., Schölkopf, B. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, 151:4972-4994, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) , March 2022 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Being a Bit Frequentist Improves Bayesian Neural Networks Kristiadi, A., Hein, M., Hennig, P. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:529-545, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Article Deep Learning for Text Style Transfer: A Survey Jin, D., Jin, Z., Hu, Z., Vechtomova, O., Mihalcea, R. Computational Linguistics, 48(1):155-205, March 2022 (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference Rendsburg, L., Kristiadi, A., Hennig, P., von Luxburg, U. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:1503-1526, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL Sontakke, S. A., Iota, S., Hu, Z., Mehrjou, A., Itti, L., Schölkopf, B. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:7518-7530, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper Pick-and-Mix Information Operators for Probabilistic ODE Solvers Bosch, N., Tronarp, F., Hennig, P. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:10015-10027, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations Krämer, N., Schmidt, J., Hennig, P. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:625-639, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper Provable Lifelong Learning of Representations Cao, X., Liu, W., Vempala, S. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:6334-6356, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper Pulling back information geometry Arvanitidis, G., Gonzalez-Duque, M., Pouplin, A., Kalatzis, D., Hauberg, S. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:4872-4894, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, March 2022 (Published) URL BibTeX

Empirical Inference Conference Paper Resampling Base Distributions of Normalizing Flows Stimper, V., Schölkopf, B., Hernández-Lobato, J. M. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 151:4915-4936, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), March 2022 (Published) arXiv URL BibTeX

Empirical Inference Article Benchmark of Data Processing Methods and Machine Learning Models for Gut Microbiome-Based Diagnosis of Inflammatory Bowel Disease Kubinski, R., Djamen-Kepaou, J., Zhanabaev, T., Hernandez-Garcia, A., Bauer, S., Hildebrand, F., Korcsmaros, T., Karam, S., Jantchou, P., Kafi, K., et al. Frontiers in Genetics, 13:784397, February 2022 (Published) DOI BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper On the Fairness of Causal Algorithmic Recourse von Kügelgen, J., Karimi, A., Bhatt, U., Valera, I., Weller, A., Schölkopf, B. Proceedings of the 36th AAAI Conference on Artificial Intelligence, 9:9584-9594, AAAI Press, Palo Alto, CA, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), February 2022, *also at ICML 2021 Workshop Algorithmic Recourse and NeurIPS 2020 Workshop Algorithmic Fairness through the Lens of Causality and Interpretability (AFCI) (Published) arXiv DOI URL BibTeX

Empirical Inference Ph.D. Thesis Variational Inference in Dynamical Systems Ialongo, A. University of Cambridge, UK, Cambridge, February 2022, (Cambridge-Tübingen-Fellowship) (Published) BibTeX

Empirical Inference Article Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation Funk, N., Schaff, C., Madan, R., Yoneda, T., Urain, J., Watson, J., Gordon, E. K., Widmaier, F., Bauer, S., Srinivasa, S. S., et al. IEEE Robotics and Automation Letters (RA-L), 7(1):478-485, January 2022 (Published) arXiv DOI URL BibTeX

Empirical Inference Article Diagnostic benefit of multiparametric MRI over contrast-enhanced CT in patients with bladder cancer: A single-center 1-year experience Hagen, F., Norz, V., Thaiss, W. M., Mair, A., Rausch, S., Bedke, J., Nikolaou, K., Stenzl, A., Kruck, S., Hepp, T., et al. European Journal of Radiology, 146, January 2022 (Published) DOI BibTeX

Empirical Inference Article Human-Robot Handshaking: A Review Prasad, V., Stock-Homburg, R., Peters, J. International Journal of Social Robotics, 14:277-293, January 2022 (Published) DOI URL BibTeX

Empirical Inference Article Artificial Intelligence in Oncological Hybrid Imaging Feuerecker, B., Heimer, M., Geyer, T., Fabritius, M. P., Gu, S., Schachtner, B., Beyer, L., Ricke, J., Gatidis, S., Ingrisch, M., et al. RöFo, 195(2):105 - 114, 2022 (Published) DOI BibTeX

Empirical Inference Book Chapter CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z. In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, :69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (Published) DOI BibTeX

Empirical Inference Book Chapter Causal Models for Dynamical Systems Peters, J., Bauer, S., Pfister, N. In Probabilistic and Causal Inference: The Works of Judea Pearl, :671-690, 1, Association for Computing Machinery, 2022 (Published) arXiv DOI BibTeX

Empirical Inference Book Chapter Causality for Machine Learning Schölkopf, B. In Probabilistic and Causal Inference: The Works of Judea Pearl, :765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (Published) arXiv DOI BibTeX

Empirical Inference Article Decoding internally generated transitions of conscious contents in the prefrontal cortex without subjective reports Kapoor, V., Dwarakanath, A., Safavi, S., Werner, J., Besserve, M., Panagiotaropoulos, T. I., Logothetis, N. K. Nature Communications, 13:1535, 2022 (Published) bioRxiv DOI URL BibTeX

Empirical Inference Article High-resolution neural network-driven mapping of multiple diffusion metrics leveraging asymmetries in the balanced steady-state free precession frequency profile Birk, F., Glang, F., Loktyushin, A., Birkl, C., Ehses, P., Scheffler, K., Heule, R. NMR in Biomedicine, 35(6):e4669, 2022 (Published) DOI BibTeX

Empirical Inference Article Identification and modelling of race driving styles Loeckel, S., Kretschia, A., van Vliet, P., Peters, J. Vehicle System Dynamics, 60(8):2890-2918, 2022 (Published) DOI URL BibTeX

Empirical Inference Miscellaneous Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning Wang, H., Jin, Z., Cao, J., Fung, G. P. C., Wong, K. 2022 (Published) arXiv BibTeX

Empirical Inference Autonomous Motion Article Learning to Play Table Tennis From Scratch using Muscular Robots Büchler, D., Guist, S., Calandra, R., Berenz, V., Schölkopf, B., Peters, J. IEEE Transactions on Robotics (T-RO), 38(6):3850-3860, 2022 (Published) arXiv Project Page Video DOI BibTeX

Empirical Inference Conference Paper Real Robot Challenge: A Robotics Competition in the Cloud Bauer, S., Wüthrich, M., Widmaier, F., Buchholz, A., Stark, S., Goyal, A., Steinbrenner, T., Akpo, J., Joshi, S., Berenz, V., et al. In Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 176:190-204, Proceedings of Machine Learning Research, (Editors: Kiela, Douwe and Ciccone, Marco and Caputo, Barbara), PMLR, NeurIPS 2021 Competitions and Demonstrations Track (NeurIPS 2021), 2022 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Book Chapter Towards Causal Algorithmic Recourse Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, :139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (Published) DOI BibTeX

Empirical Inference Conference Paper CausalNLP Tutorial: An Introduction to Causality for Natural Language Processing Jin, Z., Feder, A., Zhang, K. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP): Tutorial Abstracts, :17-22, (Editors: Samhaa R. El-Beltagy and Xipeng Qiu), Association for Computational Linguistics, 2022 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Probing as Quantifying Inductive Bias Immer*, A., Torroba Hennigen*, L., Fortuin, V., Cotterell, R. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL), 1: Long Papers:1839-1851, (Editors: Muresan, Smaranda and Nakov, Preslav and Villavicencio, Aline), Association for Computational Linguistics, May 2022, *equal contribution (Published) DOI URL BibTeX

Empirical Inference Conference Paper A Probabilistic State Space Model for Joint Inference from Differential Equations and Data Schmidt, J., Kraemer, N., Hennig, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :12374-12385, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence Kristiadi, A., Hein, M., Hennig, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :18789-18800, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Analytic Insights into Structure and Rank of Neural Network Hessian Maps Singh, S. P., Bachmann, G., Hofmann, T. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :23914-23927, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Article ArmSym: a virtual human-robot interaction laboratory for assistive robotics Bustamante, S., Peters, J., Schölkopf, B., Grosse-Wentrup, M., Jayaram, V. IEEE Transactions on Human-Machine Systems, 51(6):568-577, December 2021 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Backward-Compatible Prediction Updates: A Probabilistic Approach Träuble, F., von Kügelgen, J., Kleindessner, M., Locatello, F., Schölkopf, B., Gehler, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :116-128, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems (NeurIPS), December 2021 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Bootstrap Your Flow Midgley, L. I., Stimper, V., Simm, G. N. C., Hernández-Lobato, J. M. 1st ELLIS Machine Learning for Molecule Discovery Workshop, 1st ELLIS Machine Learning for Molecule Discovery Workshop , December 2021 (Published) arXiv URL BibTeX

Autonomous Learning Empirical Inference Conference Paper Causal Influence Detection for Improving Efficiency in Reinforcement Learning Seitzer, M., Schölkopf, B., Martius, G. In Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 34:22905-22918, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P. S. Liang and J. Wortman Vaughan), Curran Associates, Inc., Red Hook, NY, 35th Conference on Neural Information Processing Systems, December 2021 (Published) arXiv PDF Data Code URL BibTeX

Empirical Inference Conference Paper Cockpit: A Practical Debugging Tool for the Training of Deep Neural Networks Schneider, F., Dangel, F., Hennig, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :20825-20837, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems (NeurIPS), December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper DiBS: Differentiable Bayesian Structure Learning Lorch, L., Rothfuss, J., Schölkopf, B., Krause, A. In Advances in Neural Information Processing Systems 34, 29:24111-24123, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P. S. Liang and J. Wortman Vaughan), Curran Associates, Inc., Red Hook, NY, 35th Annual Conference on Neural Information Processing Systems (NeurIPS 2021), December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Dynamic Inference with Neural Interpreters Rahaman*, N., Gondal*, M. W., Joshi, S., Gehler, P., Bengio, Y., Locatello, F., Schölkopf, B. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :10985-10998, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Fine-Grained Zero-Shot Learning with DNA as Side Information Badirli, S., Akata, Z., Mohler, G., Picard, C., Dundar, M. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 34:19352-19362, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Conference on Neural Information Processing Systems (NeurIPS 2021) , December 2021 (Published) URL BibTeX

Empirical Inference Autonomous Learning Conference Paper Hierarchical Reinforcement Learning with Timed Subgoals Gürtler, N., Büchler, D., Martius, G. In Advances in Neural Information Processing Systems 34, 26:21732-21743, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P. S. Liang and J. Wortman Vaughan), Curran Associates, Inc., Red Hook, NY, 35th Conference on Neural Information Processing Systems (NeurIPS 2021), December 2021 (Published) video arXiv code URL BibTeX

Empirical Inference Conference Paper Independent mechanisms analysis, a new concept? Gresele*, L., von Kügelgen*, J., Stimper, V., Schölkopf, B., Besserve, M. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :28233-28248, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Iterative Teaching by Label Synthesis Liu, W., Liu, Z., Wang, H., Paull, L., Schölkopf, B., Weller, A. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :21681-21695, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Laplace Redux — Effortless Bayesian Deep Learning Daxberger*, E., Kristiadi*, A., Immer*, A., Eschenhagen*, R., Bauer, M., Hennig, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :20089-20103, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Linear-Time Probabilistic Solution of Boundary Value Problems Kraemer, N., Hennig, P. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :11160-11171, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Conference Paper Locality Sensitive Teaching Xu, Z., Chen, B., Li, C., Liu, W., Song, L., Lin, Y., Shrivastava, A. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :18049-18062, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX

Empirical Inference Article Real-time gravitational wave science with neural posterior estimation Dax, M., Green, S. R., Gair, J., Macke, J. H., Buonanno, A., Schölkopf, B. Physical Review Letters, 127(24), December 2021 (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper Regret Bounds for Gaussian-Process Optimization in Large Domains Wüthrich, M., Schölkopf, B., Krause, A. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :7385-7396, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) arXiv URL BibTeX

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