2024
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
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
Pace, A., Yèche, H., Schölkopf, B., Rätsch, G., Tennenholtz, G.
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
Meterez*, A., Joudaki*, A., Orabona, F., Immer, A., Rätsch, G., Daneshmand, H.
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference) Accepted
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
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
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
Jin, Z., Liu, J., Lyu, Z., Poff, S., Sachan, M., Mihalcea, R., Diab*, M., Schölkopf*, B.
Can Large Language Models Infer Causation from Correlation?
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal supervision (conference) Accepted
Donhauser, K., Lokna, J., Sanyal, A., Boedihardjo, M., Hönig, R., Yang, F.
Certified private data release for sparse Lipschitz functions
27th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024 (conference) Accepted
Schneider, J., Schumacher, P., Guist, S., Chen, L., Häufle, D., Schölkopf, B., Büchler, D.
Identifying Policy Gradient Subspaces
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
Khromov*, G., Singh*, S. P.
Some Intriguing Aspects about Lipschitz Continuity of Neural Networks
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference) Accepted
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
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
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
Imfeld*, M., Graldi*, J., Giordano*, M., Hofmann, T., Anagnostidis, S., Singh, S. P.
Transformer Fusion with Optimal Transport
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference) Accepted
Lorch, L., Krause*, A., Schölkopf*, B.
Causal Modeling with Stationary Diffusions
27th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024, *equal supervision (conference) Accepted
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
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
Theus, A., Geimer, O., Wicke, F., Hofmann, T., Anagnostidis, S., Singh, S. P.
Towards Meta-Pruning via Optimal Transport
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024 (conference) Accepted
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
Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (conference) Accepted
Zabel, S., Hennig, P., Nieselt, K.
VIPurPCA: Visualizing and Propagating Uncertainty in Principal Component Analysis
IEEE Transactions on Visualization and Computer Graphics, 30(4):2011-2022, April 2024 (article)
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)
Pals, M., Macke, J. H., Barak, O.
Trained recurrent neural networks develop phase-locked limit cycles in a working memory task
PLOS Computational Biology, 20(2), February 2024 (article)
Peisen, F., Gerken, A., Dahm, I., Nikolaou, K., Eigentler, T., Amaral, T., Moltz, J. H., Othman, A. E., Gatidis, S.
Pre-treatment 18F-FDG-PET/CT parameters as biomarkers for progression free survival, best overall response and overall survival in metastatic melanoma patients undergoing first-line immunotherapy
PLOS ONE, 19(1), January 2024 (article)
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)
Gebhard, T. D., Angerhausen, D., Konrad, B. S., Alei, E., Quanz, S. P., Schölkopf, B.
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks
Astronomy & Astrophysics, 681, 2024 (article)
Tsirtsis, S., Tabibian, B., Khajehnejad, M., Singla, A., Schölkopf, B., Gomez-Rodriguez, M.
Optimal Decision Making Under Strategic Behavior
Management Science, 2024, Published Online (article) In press
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)
Chaudhuri, A., Mancini, M., Akata, Z., Dutta, A.
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 60661-60684, (Editors: A. Oh and T. Naumann 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)
Visonà, G., Spiller, L. M., Hahn, S., Hattingen, E., Vogl, T. J., Schweikert, G., Bankov, K., Demes, M., Reis, H., Wild, P., Zeiner, P. S., Acker, F., Sebastian, M., Wenger, K. J.
Machine-Learning-Aided Prediction of Brain Metastases Development in Non-Small-Cell Lung Cancers
Clinical lung cancer, 24(8):e311-e322, December 2023 (article)
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)
Coda-Forno, J., Binz, M., Akata, Z., Botvinick, M., Wang, J. X., Schulz, E.
Meta-in-context learning in large language models
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 65189-65201, (Editors: A. Oh and T. Naumann 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)
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)
Salewski, L., Alaniz, S., Rio-Torto, I., Schulz, E., Akata, Z.
In-Context Impersonation Reveals Large Language Models’ Strengths and Biases
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 72044-72057, (Editors: A. Oh and T. Naumann 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)
von Kügelgen, J., Besserve, M., Liang, W., Gresele, L., Kekić, A., Bareinboim, E., Blei, D., Schölkopf, B.
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 48603-48638, (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)
Confavreux*, B., Ramesh*, P., Goncalves, P. J., Macke, J. H., Vogels, T. P.
Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 13545-13558, (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)
Tifrea*, A., Yüce*, G., Sanyal, A., Yang, F.
Can semi-supervised learning use all the data effectively? A lower bound perspective
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 36, pages: 21960-21982, (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)
Visonà, G., Duroux, D., Miranda, L., Sükei, E., Li, Y., Borgwardt, K., Oliver, C.
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information
Bioinformatics, 39(12), December 2023 (article)
Laumann, F., von Kügelgen, J., Park, J., Schölkopf, B., Barahona, M.
Kernel-Based Independence Tests for Causal Structure Learning on Functional Data
Entropy (Basel), 25(12), November 2023 (article)