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Empirical Inference Ph.D. Thesis Advancing Normalising Flows to Model Boltzmann Distributions Stimper, V. University of Cambridge, UK, Cambridge, June 2024, (Cambridge-Tübingen-Fellowship-Program) (Published) BibTeX
Empirical Inference Conference Paper Analyzing the Role of Semantic Representations in the Era of Large Language Models Jin*, Z., Chen*, Y., Gonzalez*, F., Liu, J., Zhang, J., Michael, J., Schölkopf, B., Diab, M. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Volume 1: Long Papers:3781-3798, (Editors: Duh, Kevin and Gomez, Helena and Bethard, Steven), Association for Computational Linguistics, June 2024, *equal contribution (Published) arXiv DOI URL BibTeX
Empirical Inference Conference Paper Automatic Generation of Model and Data Cards: A Step Towards Responsible AI Liu, J., Li, W., Jin, Z., Diab, M. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), Volume 1: Long Papers:1975-1997, (Editors: Duh, Kevin and Gomez, Helena and Bethard, Steven), Association for Computational Linguistics, June 2024 (Published) DOI URL BibTeX
Robust Machine Learning Conference Paper Does CLIP’s Generalization Performance Mainly Stem from High Train-Test Similarity? Mayilvahanan, P., Wiedemer, T., Rusak, E., Bethge, M., Brendel, W. In June 2024 (Published) ArXiv BibTeX
Robust Machine Learning Conference Paper Don’t trust your eyes: on the (un) reliability of feature visualizations Geirhos, R., Zimmermann, R. S., Bilodeau, B., Brendel, W., Kim, B. In June 2024 (Published) ArXiv BibTeX
Robust Machine Learning Article Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples Caro, J. O., Ju, Y., Pyle, R., Dey, S., Brendel, W., Anselmi, F., Patel, A. B. Frontiers in Computational Neuroscience, 18:1387077, June 2024 (Published) Frontiers in Computational Neuroscience BibTeX
Empirical Inference Conference Paper Can Large Language Models Infer Causation from Correlation? Jin, Z., Liu, J., Lyu, Z., Poff, S., Sachan, M., Mihalcea, R., Diab*, M., Schölkopf*, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal supervision (Published) arXiv URL BibTeX
Empirical Inference Conference Paper Causal Modeling with Stationary Diffusions Lorch, L., Krause*, A., Schölkopf*, B. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238:1927-1935, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024, *equal supervision (Published) URL BibTeX
Empirical Inference Conference Paper Certified private data release for sparse Lipschitz functions Donhauser, K., Lokna, J., Sanyal, A., Boedihardjo, M., Hönig, R., Yang, F. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238:1396-1404, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024 (Published) URL BibTeX
Empirical Inference Conference Paper Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding Pace, A., Yèche, H., Schölkopf, B., Rätsch, G., Tennenholtz, G. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Perceiving Systems Empirical Inference Conference Paper Ghost on the Shell: An Expressive Representation of General 3D Shapes Liu, Z., Feng, Y., Xiu, Y., Liu, W., Paull, L., Black, M. J., Schölkopf, B. In Proceedings of the Twelfth International Conference on Learning Representations (ICLR), The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) Home Code Video Project BibTeX
Empirical Inference Article Grundfragen der künstlichen Intelligenz Schölkopf, B. astronomie - Das Magazin, 42, May 2024 (Published) URL BibTeX
Empirical Inference Conference Paper Identifying Policy Gradient Subspaces Schneider, J., Schumacher, P., Guist, S., Chen, L., Häufle, D., Schölkopf, B., Büchler, D. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Autonomous Learning Conference Paper Multi-View Causal Representation Learning with Partial Observability Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., von Kügelgen, J., Locatello, F. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Conference Paper Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration ( incl. Guist, S., Schneider, J., Schölkopf, B., Büchler, D. ). IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, May 2024 (Published) arXiv DOI URL BibTeX
Empirical Inference Conference Paper Out-of-Variable Generalization for Discriminative Models Guo, S., Wildberger, J., Schölkopf, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Perceiving Systems Conference Paper Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Liu, W., Qiu, Z., Feng, Y., Xiu, Y., Xue, Y., Yu, L., Feng, H., Liu, Z., Heo, J., Peng, S., et al. In Proceedings of the Twelfth International Conference on Learning Representations (ICLR), The Twelfth International Conference on Learning Representations, May 2024 (Published) Home Code HuggingFace project URL BibTeX
Empirical Inference Conference Paper Skill or Luck? Return Decomposition via Advantage Functions Pan, H., Schölkopf, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Conference Paper Some Intriguing Aspects about Lipschitz Continuity of Neural Networks Khromov*, G., Singh*, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Conference Paper Stochastic Gradient Descent for Gaussian Processes Done Right Lin*, J. A., Padhy*, S., Antorán*, J., Tripp, A., Terenin, A., Szepesvari, C., Hernández-Lobato, J. M., Janz, D. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Conference Paper Targeted Reduction of Causal Models Kekić, A., Schölkopf, B., Besserve, M. ICLR 2024 Workshop on AI4DifferentialEquations In Science, May 2024 (Published) URL BibTeX
Empirical Inference Autonomous Learning Conference Paper The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks Spieler, A., Rahaman, N., Martius, G., Schölkopf, B., Levina, A. In The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Conference Paper Towards Meta-Pruning via Optimal Transport Theus, A., Geimer, O., Wicke, F., Hofmann, T., Anagnostidis, S., Singh, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Conference Paper Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion Meterez*, A., Joudaki*, A., Orabona, F., Immer, A., Rätsch, G., Daneshmand, H. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Conference Paper Transformer Fusion with Optimal Transport Imfeld*, M., Graldi*, J., Giordano*, M., Hofmann, T., Anagnostidis, S., Singh, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Master Thesis Algorithmic Compositional Learning of Language Models Thomm, J. ETH Zurich, Switzerland, April 2024 (Published) BibTeX
Empirical Inference Miscellaneous Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA Gupte, N., Ramos-Buades, A., Buonanno, A., Gair, J., Miller, M. C., Dax, M., Green, S. R., Pürrer, M., Wildberger, J., Macke, J. H., et al. April 2024 (Published) URL BibTeX
Empirical Inference Conference Paper PILLAR: How to make semi-private learning more effective Pinto, F., Hu, Y., Yang, F., Sanyal, A. 2nd IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 110-139, April 2024 (Published) DOI BibTeX
Empirical Inference Article SimReadUntil for benchmarking selective sequencing algorithms on ONT devices Mordig, M., Ratsch, G., Kahles, A. Bioinformatics, 40(5):btae199, April 2024 (Published) DOI URL BibTeX
Empirical Inference Article VIPurPCA: Visualizing and Propagating Uncertainty in Principal Component Analysis Zabel, S., Hennig, P., Nieselt, K. IEEE Transactions on Visualization and Computer Graphics, 30(4):2011-2022, April 2024 (Published) DOI BibTeX
Empirical Inference Poster Koopman Spectral Analysis Uncovers the Temporal Structure of Spontaneous Neural Events Shao, K., Xu, Y., Logothetis, N., Shen, Z., Besserve, M. Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (Published) URL BibTeX
Robust Machine Learning Conference Paper An interventional perspective on identifiability in gaussian lti systems with independent component analysis Rajendran, G., Reizinger, P., Brendel, W., Ravikumar, P. K. 41-70, Causal Learning and Reasoning, March 2024 (Published) PMLR BibTeX
Empirical Inference Master Thesis Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability Ortu, F. University of Trieste, Italy, March 2024 (Published) BibTeX
Empirical Inference Article Learning Graph Embeddings for Open World Compositional Zero-Shot Learning Mancini, M., Naeem, M. F., Xian, Y., Akata, Z. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(3):1545-1560, IEEE, New York, NY, March 2024 (Published) DOI BibTeX
Empirical Inference Poster LFP transient events in macaque subcortical areas reveal network coordination across scales and structures: a simultaneous fMRI-electrophysiology study Besserve, M., Safavi, S., Schölkopf, B., Logothetis, N. Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (Published) URL BibTeX
Deep Models and Optimization Conference Paper SDEs for Minimax Optimization Monzio Compagnoni, E., Orvieto, A., Kersting, H., Proske, F., Lucchi, A. PMLR, AISTATS, February 2024 (Published) URL BibTeX
Empirical Inference Ph.D. Thesis Identifiable Causal Representation Learning: Unsupervised, Multi-View, and Multi-Environment von Kügelgen, J. University of Cambridge, UK, Cambridge, February 2024, (Cambridge-Tübingen-Fellowship) (Published) URL BibTeX
Empirical Inference Conference Paper Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling Gebhard, T. D., Wildberger, J., Dax, M., Angerhausen, D., Quanz, S. P., Schölkopf, B. 3rd Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE), February 2024 (Published) arXiv URL BibTeX
Empirical Inference Ph.D. Thesis Methods for Generative Modeling and Interpretable Classification with Strong Differential Privacy Harder, F. University of Tübingen, Germany, February 2024, IMPRS-PhD-Program (Published) URL BibTeX
Empirical Inference Article Trained recurrent neural networks develop phase-locked limit cycles in a working memory task Pals, M., Macke, J. H., Barak, O. PLOS Computational Biology, 20(2), February 2024 (Published) DOI BibTeX
Deep Models and Optimization Conference Paper Recurrent Distance Filtering for Graph Representation Learning Ding, Y., Orvieto, A., He, B., Hofmann, T. In PMLR, ICML, January 2024 (Published) URL BibTeX
Deep Models and Optimization Conference Paper Super Consistency of Neural Network Landscapes and Learning Rate Transfer Noci, L., Meterez, A., Hofmann, T., Orvieto, A. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems, Thirty-Eighth Annual Conference on Neural Information Processing Systems, January 2024 (Published) URL BibTeX
Social Foundations of Computation Algorithms and Society Conference Paper Causal Inference out of Control: Estimating Performativity without Treatment Randomization Cheng, G., Hardt, M., Mendler-Dünner, C. In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), PMLR, The Forty-First International Conference on Machine Learning (ICML), January 2024 (Published) ArXiv URL BibTeX
Robust Machine Learning Conference Paper Effective pruning of web-scale datasets based on complexity of concept clusters Abbas, A., Rusak, E., Tirumala, K., Brendel, W., Chaudhuri, K., Morcos, A. S. In January 2024 (Published) ArXiv BibTeX
Empirical Inference Conference Paper Multi-channel free space optical convolutions with incoherent light Song, A., Kottapalli, S. N. M., Schölkopf, B., Fischer, P. AI and Optical Data Sciences V, PC12903:PC129030I, (Editors: Ken-ichi Kitayama and Volker J. Sorger), SPIE, January 2024 (Published) DOI BibTeX
Empirical Inference Article Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery Visonà, G., Bouzigon, E., Demenais, F., Schweikert, G. Briefings in Bioinformatics, 25(2), January 2024 (Published) DOI BibTeX
Empirical Inference Optics and Sensing Laboratory Conference Paper Polarization-based non-linear deep diffractive neural networks Kottapalli, S. N. M., Schlieder, L., Song, A., Volchkov, V., Schölkopf, B., Fischer, P. AI and Optical Data Sciences V, PC12903:PC129030B, (Editors: Ken-ichi Kitayama and Volker J. Sorger), SPIE, January 2024 (Published) DOI BibTeX
Empirical Inference Article 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 Peisen, F., Gerken, A., Dahm, I., Nikolaou, K., Eigentler, T., Amaral, T., Moltz, J. H., Othman, A. E., Gatidis, S. PLOS ONE, 19(1), January 2024 (Published) DOI BibTeX
Empirical Inference Article Towards fully covariant machine learning Villar, S., Hogg, D. W., Yao, W., Kevrekidis, G. A., Schölkopf, B. Transactions on Machine Learning Research, January 2024 (Published) URL BibTeX
Empirical Inference Miscellaneous Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models Rajendran, G., Buchholz, S., Aragam, B., Schölkopf, B., Ravikumar, P. 2024 (Published) arXiv BibTeX