Empirical Inference Robust Machine Learning Conference Paper Provably Learning Object-Centric Representations Brady*, J., Zimmermann*, R. S., Sharma, Y., Schölkopf, B., von Kügelen, J., Brendel, W. Proceedings of the 40th International Conference on Machine Learning (ICML), 202:3038-3062, Proceedings of Machine Learning Research, (Editors: A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato and J. Scarlett), JMLR, Cambridge, MA, July 2023, *equal contribution (Published) URL BibTeX

Empirical Inference Article Evaluating vaccine allocation strategies using simulation-assisted causal modeling Kekić, A., Dehning, J., Gresele, L., von Kügelgen, J., Priesemann, V., Schölkopf, B. Patterns, 4(6), June 2023 (Published) DOI URL BibTeX

Empirical Inference Conference Paper DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability Eastwood*, C., Nicolicioiu*, A. L., von Kügelgen*, J., Kekić, A., Träuble, F., Dittadi, A., Schölkopf, B. The Eleventh International Conference on Learning Representations (ICLR), May 2023, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Backtracking Counterfactuals von Kügelgen, J., Mohamed, A., Beckers, S. Proceedings of the Second Conference on Causal Learning and Reasoning (CLeaR), 213:177-196, Proceedings of Machine Learning Research, (Editors: van der Schaar, Mihaela and Zhang, Cheng and Janzing, Dominik), PMLR, April 2023 (Published) URL BibTeX

Empirical Inference Conference Paper Unsupervised Object Learning via Common Fate Tangemann, M., Schneider, S., von Kügelgen, J., Locatello, F., Gehler, P., Brox, T., Kümmerer, M., Bethge, M., Schölkopf, B. Proceedings of the Second Conference on Causal Learning and Reasoning (CLeaR), 213:281-327, Proceedings of Machine Learning Research, (Editors: van der Schaar, Mihaela and Zhang, Cheng and Janzing, Dominik), PMLR, April 2023 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Active Bayesian Causal Inference Toth, C., Lorch, L., Knoll, C., Krause, A., Pernkopf, F., Peharz*, R., von Kügelgen*, J. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 35:16261-16275, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), December 2022, *shared last author (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Perry, R., von Kügelgen*, J., Schölkopf*, B. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 10904-10917, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), December 2022, *shared last author (Published) arXiv URL BibTeX

Empirical Inference Autonomous Learning Robust Machine Learning Conference Paper Embrace the Gap: VAEs Perform Independent Mechanism Analysis Reizinger*, P., Gresele*, L., Brady*, J., von Kügelgen, J., Zietlow, D., Schölkopf, B., Martius, G., Brendel, W., Besserve, M. Advances in Neural Information Processing Systems (NeurIPS 2022), 35:12040-12057, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Annual Conference on Neural Information Processing Systems, December 2022, *equal first authorship (Published) Arxiv PDF URL BibTeX

Empirical Inference Conference Paper Probable Domain Generalization via Quantile Risk Minimization Eastwood, C., Robey, A., Singh, S., von Kügelgen, J., Hassani, H., Pappas, G. J., Schölkopf, B. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 35:17340-17358, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Annual Conference on Neural Information Processing Systems, December 2022 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Causal Inference Through the Structural Causal Marginal Problem Gresele*, L., von Kügelgen*, J., Kübler*, J. M., Kirschbaum, E., Schölkopf, B., Janzing, D. Proceedings of the 39th International Conference on Machine Learning (ICML), 162:7793-7824, (Editors: Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan), PMLR, July 2022, *equal contribution (Published) URL BibTeX