2024
Beck, J., Bosch, N., Deistler, M., Kadhim, K. L., Macke, J. H., Hennig, P., Berens, P.
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for ODEs
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Chen*, W., Zhang*, M., Paige, B., Hernández-Lobato, J. M., Barber, D.
Diffusive Gibbs Sampling
41st Conference on Machine Learning (ICML), July 2024, *equal contribution (conference) Accepted
Schröder, C., Macke, J. H.
Simultaneous identification of models and parameters of scientific simulators
41st Conference on Machine Learning (ICML), Vienna, Austria, July 2024 (conference) Accepted
Dmitriev, D., Szabó, K., Sanyal, A.
On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective
Proceedings of the 37th Annual Conference on Learning Theory (COLT), 247, pages: 1379-1398, Proceedings of Machine Learning Research, (Editors: Agrawal, Shipra and Roth, Aaron), PMLR, July 2024, (talk) (conference)
Bouchiat, K., Immer, A., Yèche, H., Rätsch, G., Fortuin, V.
Improving Neural Additive Models with Bayesian Principles
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., Magliacane, S.
A Sparsity Principle for Partially Observable Causal Representation Learning
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Guist, S., Schneider, J., Ma, H., Chen, L., Berenz, V., Martus, J., Ott, H., Grüninger, F., Muehlebach, M., Fiene, J., Schölkopf, B., Büchler, D.
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion
Robotics: Science and Systems, July 2024 (conference) Accepted
Kekic, A., Schölkopf, B., Besserve, M.
Targeted Reduction of Causal Models
40th Conference on Uncertainty in Artificial Intelligence (UAI), July 2024 (conference) Accepted
Kremer, H., Schölkopf, B.
Geometry-Aware Instrumental Variable Regression
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Hu, Y., Sanyal, A., Schölkopf, B.
Provable Privacy with Non-Private Pre-Processing
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Buchholz, S., Park, J., Schölkopf, B.
Products, Abstractions and Inclusions of Causal Spaces
40th Conference on Uncertainty in Artificial Intelligence (UAI), July 2024 (conference) Accepted
Opedal, A., Stolfo, A., Shirakami, H., Jiao, Y., Cotterell, R., Schölkopf, B., Saparov, A., Sachan, M.
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Ben-Dov*, O., Fawkes*, J., Samadi, S., Sanyal, A.
The Role of Learning Algorithms in Collective Action
41st Conference on Machine Learning (ICML), July 2024, *equal contribution (conference) Accepted
Gloeckler, M., Deistler, M., Weilbach, C. D., Wood, F., Macke, J. H.
All-in-one simulation-based inference
41st Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Gao, G., Liu, W., Chen, A., Geiger, A., Schölkopf, B.
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2024 (conference) Accepted
Guo, S., Wildberger, J., Schölkopf, B.
Out-of-Variable Generalization for Discriminative Models
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Pace, A., Yèche, H., Schölkopf, B., Rätsch, G., Tennenholtz, G.
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Meterez*, A., Joudaki*, A., Orabona, F., Immer, A., Rätsch, G., Daneshmand, H.
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference)
Open X-Embodiment Collaboration ( incl. Guist, S., Schneider, J., Schölkopf, B., Büchler, D. ).
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
IEEE International Conference on Robotics and Automation (ICRA), May 2024 (conference) Accepted
Donhauser, K., Lokna, J., Sanyal, A., Boedihardjo, M., Hönig, R., Yang, F.
Certified private data release for sparse Lipschitz functions
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238, pages: 1396-1404, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024 (conference)
Spieler, A., Rahaman, N., Martius, G., Schölkopf, B., Levina, A.
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Jin, Z., Liu, J., Lyu, Z., Poff, S., Sachan, M., Mihalcea, R., Diab*, M., Schölkopf*, B.
Can Large Language Models Infer Causation from Correlation?
The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal supervision (conference)
Liu, Z., Feng, Y., Xiu, Y., Liu, W., Paull, L., Black, M. J., Schölkopf, B.
Ghost on the Shell: An Expressive Representation of General 3D Shapes
In Proceedings of the Twelfth International Conference on Learning Representations, The Twelfth International Conference on Learning Representations, May 2024 (inproceedings) Accepted
Schneider, J., Schumacher, P., Guist, S., Chen, L., Häufle, D., Schölkopf, B., Büchler, D.
Identifying Policy Gradient Subspaces
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Khromov*, G., Singh*, S. P.
Some Intriguing Aspects about Lipschitz Continuity of Neural Networks
The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference)
Liu, W., Qiu, Z., Feng, Y., Xiu, Y., Xue, Y., Yu, L., Feng, H., Liu, Z., Heo, J., Peng, S., Wen, Y., Black, M. J., Weller, A., Schölkopf, B.
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
In Proceedings of the Twelfth International Conference on Learning Representations, The Twelfth International Conference on Learning Representations, May 2024 (inproceedings) Accepted
Pan, H., Schölkopf, B.
Skill or Luck? Return Decomposition via Advantage Functions
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Imfeld*, M., Graldi*, J., Giordano*, M., Hofmann, T., Anagnostidis, S., Singh, S. P.
Transformer Fusion with Optimal Transport
The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference)
Lorch, L., Krause*, A., Schölkopf*, B.
Causal Modeling with Stationary Diffusions
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238, pages: 1927-1935, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024, *equal supervision (conference)
Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., von Kügelgen, J., Locatello, F.
Multi-View Causal Representation Learning with Partial Observability
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Theus, A., Geimer, O., Wicke, F., Hofmann, T., Anagnostidis, S., Singh, S. P.
Towards Meta-Pruning via Optimal Transport
The Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference)
Lin*, J. A., Padhy*, S., Antorán*, J., Tripp, A., Terenin, A., Szepesvari, C., Hernández-Lobato, J. M., Janz, D.
Stochastic Gradient Descent for Gaussian Processes Done Right
The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference)
Pinto, F., Hu, Y., Yang, F., Sanyal, A.
PILLAR: How to make semi-private learning more effective
2nd IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), pages: 110-139, April 2024 (conference)
von Kügelgen, J.
Identifiable Causal Representation Learning
University of Cambridge, UK, Cambridge, February 2024, (Cambridge-Tübingen-Fellowship) (phdthesis)
Kottapalli, S. N. M., Schlieder, L., Song, A., Volchkov, V., Schölkopf, B., Fischer, P.
Polarization-based non-linear deep diffractive neural networks
AI and Optical Data Sciences V, PC12903, pages: PC129030B, (Editors: Ken-ichi Kitayama and Volker J. Sorger), SPIE, January 2024 (conference)
Song, A., Kottapalli, S. N. M., Schölkopf, B., Fischer, P.
Multi-channel free space optical convolutions with incoherent light
AI and Optical Data Sciences V, PC12903, pages: PC129030I, (Editors: Ken-ichi Kitayama and Volker J. Sorger), SPIE, January 2024 (conference)
2023
Eastwood*, C., Singh*, S., Nicolicioiu, A. L., Vlastelica, M., von Kügelgen, J., Schölkopf, B.
Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 18291-18324, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Jin*, Z., Chen*, Y., Leeb*, F., Gresele*, L., Kamal, O., Lyu, Z., Blin, K., Gonzalez, F., Kleiman-Weiner, M., Sachan, M., Schölkopf, B.
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 31038-31065, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *main contributors (conference)
Gao*, R., Deistler*, M., Macke, J. H.
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 80191-80219, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Kuznetsova*, R., Pace*, A., Burger*, M., Yèche, H., Rätsch, G.
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series
Proceedings of the 3rd Machine Learning for Health Symposium (ML4H) , 225, pages: 268-291, Proceedings of Machine Learning Research, (Editors: Hegselmann, S.and Parziale, A. and Shanmugam, D. and Tang, S. and Asiedu, M. N. and Chang, S. and Hartvigsen, T. and Singh, H.), PMLR, December 2023, *equal contribution (conference)
Qiu*, Z., Liu*, W., Feng, H., Xue, Y., Feng, Y., Liu, Z., Zhang, D., Weller, A., Schölkopf, B.
Controlling Text-to-Image Diffusion by Orthogonal Finetuning
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 79320-79362, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Guo*, S., Tóth*, V., Schölkopf, B., Huszár, F.
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 36463-36475, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Lin*, J. A., Antorán*, J., Padhy*, S., Janz, D., Hernández-Lobato, J. M., Terenin, A.
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 36886-36912, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Midgley*, L. I., Stimper*, V., Antorán*, J., Mathieu*, E., Schölkopf, B., Hernández-Lobato, J. M.
SE(3) Equivariant Augmented Coupling Flows
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 79200-79225, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Wildberger*, J., Dax*, M., Buchholz*, S., Green, S. R., Macke, J. H., Schölkopf, B.
Flow Matching for Scalable Simulation-Based Inference
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 16837-16864, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Buchholz*, S., Rajendran*, G., Rosenfeld, E., Aragam, B., Schölkopf, B., Ravikumar, P.
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 45419-45462, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *equal contribution (conference)
Munkhoeva, M., Oseledets, I.
Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 60712-60723, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023 (conference)
Lorch, L., Krause*, A., Schölkopf*, B.
Causal Modeling with Stationary Diffusions
Causal Representation Learning Workshop at NeurIPS 2023, December 2023, *equal supervision (conference)
Liang, W., Kekić, A., von Kügelgen, J., Buchholz, S., Besserve, M., Gresele*, L., Schölkopf*, B.
Causal Component Analysis
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 32481-32520, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023, *shared last author (conference)
Park, J., Buchholz, S., Schölkopf, B., Muandet, K.
A Measure-Theoretic Axiomatisation of Causality
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 28510-28540, (Editors: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine), Curran Associates, Inc., 37th Annual Conference on Neural Information Processing Systems, December 2023 (conference)