2024
Schumacher, P., Krause, L., Schneider, J., Büchler, D., Martius, G., Haeufle, D.
Learning to Control Emulated Muscles in Real Robots: Towards Exploiting Bio-Inspired Actuator Morphology
In 10th International Conference on Biomedical Robotics and Biomechatronics (BioRob), September 2024 (inproceedings) Accepted
Wu*, W., Chen*, W., Zhang, C., Woodland, P. C.
Modelling Variability in Human Annotator Simulation
62nd Annual Meeting of the Association for Computational Linguistics (ACL), August 2024, *equal contribution (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)
Buchholz, S., Schölkopf, B.
Robustness of Nonlinear Representation Learning
41st International 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 International 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 International Conference on Machine Learning (ICML), Vienna, Austria, July 2024 (conference) Accepted
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 International Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Jain, S., Lubana, E. S., Oksuz, K., Joy, T., Torr, P. H. S., Sanyal, A., Dokania, P. K.
What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study
ICML 2024 Workshop on Mechanistic Interpretability (Spotlight), July 2024 (conference) Accepted
Reizinger, P., Ujváry, S., Mészáros, A., Kerekes, A., Brendel, W., Huszár, F.
Position: Understanding LLMs Requires More Than Statistical Generalization
41st International Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Bouchiat, K., Immer, A., Yèche, H., Rätsch, G., Fortuin, V.
Improving Neural Additive Models with Bayesian Principles
41st International Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Abdolahpourrostam, A., Sanyal, A., Moosavi-Dezfooli, S.
Unveiling CLIP Dynamics: Linear Mode Connectivity and Generalization
ICML 2024 Workshop on Foundation Models in the Wild, 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 International Conference on Machine Learning (ICML), 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 International 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
Keurti, H., Schölkopf, B., Aceituno, P. V., Grewe, B.
Stitching Manifolds: Leveraging Interaction to Compose Object Representations into Scenes
ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM), July 2024 (conference) Accepted
Park, J.
A Measure-Theoretic Axiomatisation of Causality and Kernel Regression
University of Tübingen, Germany, July 2024 (phdthesis)
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
Hu, Y., Sanyal, A., Schölkopf, B.
Provable Privacy with Non-Private Pre-Processing
41st International Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Sajjadi, S. M. M.
Enhancement and Evaluation of Deep Generative Networks with Applications in Super-Resolution and Image Generation
University of Tübingen, Germany, July 2024 (phdthesis)
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 International 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 International Conference on Machine Learning (ICML), July 2024, *equal contribution (conference) Accepted
Sanyal, A., Hu, Y., Yu, Y., Ma, Y., Wang, Y., Schölkopf, B.
Accuracy on the wrong line: On the pitfalls of noisy data for OOD generalisation
ICML 2024 Next Generation of AI Safety Workshop (Oral), July 2024 (conference) Accepted
Zheng, Y., Tang, Z., Qiu, Y., Schölkopf, B., Zhang, K.
Detecting and Identifying Selection Structure in Sequential Data
41st International Conference on Machine Learning (ICML), July 2024 (conference) Accepted
Gloeckler, M., Deistler, M., Weilbach, C. D., Wood, F., Macke, J. H.
All-in-one simulation-based inference
41st International 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
Jin*, Z., Chen*, Y., Gonzalez*, F., Liu, J., Zhang, J., Michael, J., Schölkopf, B., Biab, M.
Analyzing the Role of Semantic Representations in the Era of Large Language Models
2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics, June 2024, *equal contribution (conference) Accepted
Stimper, V.
Advancing Normalising Flows to Model Boltzmann Distributions
University of Cambridge, UK, Cambridge, June 2024, (Cambridge-Tübingen-Fellowship-Program) (phdthesis)
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)
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)
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)
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
In The Twelfth International Conference on Learning Representations (ICLR), May 2024 (inproceedings)
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
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)