Publications

Empirical Inference Conference Paper CauSciBench: Assessing LLM Causal Reasoning for Scientific Research Acharya, S., Zhang, T. J., Kim, A., Haghighat, A., Xianlin, S., Shrestha, B., Mordig, M., Danisman, F., Jose, C., Qi, Y., et al. NeurIPS 2025 Workshop on CauScien: Uncovering Causality in Science, December 2025 (Accepted) BibTeX

Empirical Inference Conference Paper Cultural Alien Sampler: Open-ended art generation balancing originality and coherence Hernandez, A., Yakura, H., Brinkmann, L., Sola, M. C., Alhaija, H. A., Serna, I., Rahaman, N., Schölkopf, B., Rahwan, I. Advances in Neural Information Processing Systems 38 (NeurIPS 2025), 39th Annual Conference on Neural Information Processing Systems, Creative AI Track, December 2025 (Accepted) arXiv BibTeX

Empirical Inference Conference Paper Do-PFN: In-Context Learning for Causal Effect Estimation Robertson*, J., Reuter*, A., Guo, S., Hollmann, N., Hutter, F., Schölkopf, B. Advances in Neural Information Processing Systems 38 (NeurIPS 2025), 39th Annual Conference on Neural Information Processing Systems, December 2025, *equal contribution (Accepted) arXiv BibTeX

Haptic Intelligence Autonomous Learning Empirical Inference Conference Paper Adding Internal Audio Sensing to Internal Vision Enables Human-Like In-Hand Fabric Recognition with Soft Robotic Fingertips Andrussow, I., Solano Vega, L. J., Richardson, B. A., Martius, G., Kuchenbecker, K. J. In Proceedings of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), Seoul, Korea, September 2025 (Accepted) BibTeX

Empirical Inference Conference Paper Active Fine-Tuning of Multi-Task Policies Bagatella, M., Hübotter, J., Martius, G., Krause, A. In Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:2409-2441, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Empirical Inference Deep Models and Optimization Conference Paper Generalized Interpolating Discrete Diffusion von Rütte, D., Fluri, J., Ding, Y., Orvieto, A., Schölkopf, B., Hofmann, T. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:61810-61843, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Generative Intervention Models for Causal Perturbation Modeling Schneider, N., Lorch, L., Kilbertus, N., Schölkopf, B., Krause, A. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:53388-53412, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models Kekić, A., Garrido Mejia, S., Schölkopf, B. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:29651-29669, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Position: Probabilistic Modelling is Sufficient for Causal Inference Mlodozeniec, B. K., Krueger, D., Turner, R. E. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:81810-81840, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) URL BibTeX

Empirical Inference Conference Paper Progressive Tempering Sampler with Diffusion Rissanen*, S., OuYang*, R., He*, J., Chen, W., Heinonen, M., Solin, A., Hernández-Lobato, J. M. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:51724-51746, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Autonomous Learning Conference Paper SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models Sancaktar, C., Gumbsch, C., Zadaianchuk, A., Kolev, P., Martius, G. In Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:52745-52777, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), International Conference on Machine Learning , July 2025 (Published) arXiv Project website URL BibTeX

Empirical Inference Conference Paper Scalable Gaussian Processes with Latent Kronecker Structure Lin, J. A., Ament, A., Balandat, M., Eriksson, D., Hernández-Lobato, J. M., Bakshy, E. Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:37730-37744, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Autonomous Learning Empirical Inference Conference Paper Zero-Shot Offline Imitation Learning via Optimal Transport Rupf, T., Bagatella, M., Gürtler, N., Frey, J., Martius, G. In Proceedings of the 42nd International Conference on Machine Learning (ICML), 267:52345-52381, Proceedings of Machine Learning Research, (Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry), PMLR, International Conference on Machine Learning, July 2025 (Published) arXiv URL BibTeX

Empirical Inference Article Flow annealed importance sampling bootstrap meets differentiable particle physics Kofler, A., Stimper, V., Mikhasenko, M., Kagan, M., Heinrich, L. Machine Learning: Science and Technology, 6(2), IOP Publishing, June 2025 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Temporally Consistent Object-Centric Learning by Contrasting Slots Manasyan, A., Seitzer, M., Radovic, F., Martius, G., Zadaianchuk, A. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5401-5411, June 2025 (Published) DOI BibTeX

Empirical Inference Conference Paper VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models Ye, M., Liu, W., He, P. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8679-8688, June 2025 (Published) DOI BibTeX

Empirical Inference Perceiving Systems Conference Paper ChatHuman: Chatting about 3D Humans with Tools Lin, J., Feng, Y., Liu, W., Black, M. J. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8150-8161, June 2025 (Published) project pdf Paper DOI BibTeX

Empirical Inference Conference Paper Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation Sanyal, A., Hu, Y., Yu, Y., Ma, Y., Wang, Y., Schölkopf, B. Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 258:2170-2178, Proceedings of Machine Learning Research, (Editors: Li, Yingzhen and Mandt, Stephan and Agrawal, Shipra and Khan, Emtiyaz), PMLR, May 2025 (Published) URL BibTeX

Empirical Inference Conference Paper Training Neural Samplers with Reverse Diffusive KL Divergence He*, J., Chen*, W., Zhang*, M., Barber, D., Hernández-Lobato, J. M. Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 258:5167-5175, Proceedings of Machine Learning Research, (Editors: Li, Yingzhen and Mandt, Stephan and Agrawal, Shipra and Khan, Emtiyaz), PMLR, May 2025, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector Zhang, A., Xiao, T. Z., Liu, W., Bamler, R., Wischik, D. Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 258:2701-2709, Proceedings of Machine Learning Research, (Editors: Li, Yingzhen and Mandt, Stephan and Agrawal, Shipra and Khan, Emtiyaz), PMLR, May 2025 (Published) URL BibTeX

Empirical Inference Autonomous Learning Conference Paper Advancing Out-of-Distribution Detection via Local Neuroplasticity Canevaro, A., Schmidt, J., Marvi, M. S., Yu, H., Martius, G., Jordan, J. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Perceiving Systems Conference Paper Can Large Language Models Understand Symbolic Graphics Programs? Qiu, Z., Liu, W., Feng, H., Liu, Z., Xiao, T. Z., Collins, K. M., Tenenbaum, J. B., Weller, A., Black, M. J., Schölkopf, B. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv Paper BibTeX

Empirical Inference Conference Paper Compositional simulation-based inference for time series Gloeckler*, M., Toyota*, S., Fukumizu, K., Macke, J. H. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Learning and Dynamical Systems Conference Paper Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering Kladny, K., Schölkopf, B., Muehlebach, M. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv URL BibTeX

Empirical Inference Robust Machine Learning Conference Paper Cross-Entropy Is All You Need to Invert the Data Generating Process Reizinger*, P., Bizeul*, A., Juhos*, A., Vogt, J. E., Balestriero, R., Brendel, W., Klindt, D. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *Joint first authorship (Published) arXiv BibTeX

Empirical Inference Conference Paper Differential private steering for Large language model alignment Goel, A., Hu, Y., Gurevych, I., Sanyal, A. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Perceiving Systems Conference Paper Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Liu, Z., Xiao, T. Z., Liu, W., Bengio, Y., Zhang, D. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Robust Machine Learning Conference Paper Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning Reizinger, P., Guo, S., Huszár, F., Schölkopf, B., Brendel, W. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Conference Paper Improving Probabilistic Diffusion Models With Optimal Covariance Matching Ou*, Z., Zhang*, M., Zhang, A., Xiao, T. Z., Li, Y., Barber, D. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *equal contribution (Published) arXiv BibTeX

Empirical Inference Conference Paper Influence Functions for Scalable Data Attribution in Diffusion Models Mlodozeniec, B. K., Eschenhagen, R., Bae, J., Immer, A., Krueger, D., Turner, R. E. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Robust Machine Learning Conference Paper Interaction Asymmetry: A General Principle for Learning Composable Abstractions Brady, J., von Kügelgen, J., Lachapelle, S., Buchholz, S., Kipf*, T., Brendel*, W. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *joint senior author (Published) arXiv BibTeX

Empirical Inference Conference Paper Language Model Alignment in Multilingual Trolley Problems Jin, Z., Kleiman-Weiner, M., Piatti, G., Levine, S., Liu, J., Gonzalez, F., Ortu, F., Strausz, A., Sachan, M., Mihalcea, R., et al. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Autonomous Learning Conference Paper On the Transfer of Object-Centric Representation Learning Didolkar, A. R., Zadaianchuk, A., Goyal, A., Mozer, M. C., Bengio, Y., Martius*, G., Seitzer*, M. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Preference Elicitation for Offline Reinforcement Learning Pace, A., Schölkopf, B., Rätsch, G., Ramponi, G. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Conference Paper Standardizing Structural Causal Models Ormaniec*, W., Sussex*, S., Lorch*, L., Schölkopf, B., Krause, A. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *equal contribution (Published) arXiv BibTeX

Empirical Inference Conference Paper The Directionality of Optimization Trajectories in Neural Networks Singh, S. P., He, B., Hofmann, T., Schölkopf, B. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) URL BibTeX

Empirical Inference Conference Paper What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis Ormaniec, W., Dangel, F., Singh, S. P. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX

Empirical Inference Conference Paper Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone Mihalcea*, R., Ignat*, O., Bai, L., Borah, A., Chiruzzo, L., Jin, Z., Kwizera, C., Nwatu, J., Poria, S., Solorio, T. The Thirty-Nineth AAAI Conference on Artificial Intelligence, AAAI 2025 (Senior Member Presentation Track), (27)28657-28670, (Editors: Toby Walsh, Julie Shah, Zico Kolter ), AAAI Press, April 2025, *equal contribution (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs Opedal*, A., Shirakami*, H., Schölkopf, B., Saparov, A., Sachan, M. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *equal contribution (Published) arXiv BibTeX

Empirical Inference Ph.D. Thesis Learning to Generalize Across Distribution Shifts Träuble, F. J. University of Tübingen, Germany, March 2025, (IMPRS-PhD-Fellowship-Program and ELLIS-PhD-Fellowship-Program) (Published) BibTeX

Empirical Inference Article Real-time inference for binary neutron star mergers using machine learning Dax, M., Green, S. R., Gair, J., Gupte, N., Pürrer, M., Raymond, V., Wildberger, J., Macke, J. H., Buonanno, A., Schölkopf, B. Nature, 639(8053):49-53, March 2025 (Published) DOI URL BibTeX

Empirical Inference Article Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels Gebhard, T. D., Wildberger, J., Dax, M., Kofler, A., Angerhausen, D., Quanz, S., Schölkopf, B. Astronomy \& Astrophysics, 693, January 2025 (Published) DOI URL BibTeX

Empirical Inference Article In silico biological discovery with large perturbation models Miladinovic*, D., Höppe*, T., Chevalley, M., Georgiou, A., Stuart, L., Mehrjou, A., Bantscheff, M., Schölkopf, B., Schwab, P. Nature Computational Science, October 2025, *equal contribution (Published) DOI URL BibTeX

Empirical Inference Conference Paper A data and task-constrained mechanistic model of the mouse outer retina shows robustness to contrast variations Kadhim, K. L., Beck, J., Huang, Z., Macke, J. H., Rieke, F., Euler, T., Deistler, M., Berens, P. Advances in Neural Information Processing Systems 38 (NeurIPS 2025), 39th Annual Conference on Neural Information Processing Systems, December 2025 (Accepted) bioRxiv BibTeX

Empirical Inference Article Artificial intelligence for modelling infectious disease epidemics Kraemer, M. U. G., Tsui, J. L., Chang, S. Y., Lytras, S., Khurana, M. P., Vanderslott, S., Bajaj, S., Scheidwasser, N., Curran-Sebastian, J. L., Semenova, E., et al. Nature, 638(8051):623-635, February 2025 (Published) DOI URL BibTeX

Empirical Inference Ph.D. Thesis Bridging Deep Learning and Probabilistic Inference: Towards Data Efficiency, Identifiability, and Sampling Scalability Chen, W. University of Cambridge, UK, June 2025, (Cambridge-Tübingen-Fellowship) (Published) BibTeX

Empirical Inference Conference Paper CauSciBench: Benchmarking LLM Causal Reasoning for Scientific Research Zhang, T. J., Acharya, S., Kim, A., Haghighat, A., Shrestha, R. B., Jose, C., Qi, Y., Cobben, P., Mordig, M., He, P., et al. MathNLP 2025: The 3rd Workshop on Mathematical Natural Language Processing at EMNLP, November 2025 (Accepted) BibTeX

Empirical Inference Conference Paper Counterfactual reasoning: an analysis of in-context emergence Miller, M., Schölkopf, B., Guo, S. Advances in Neural Information Processing Systems 38 (NeurIPS 2025), 39th Annual Conference on Neural Information Processing Systems, December 2025 (Accepted) arXiv BibTeX

Empirical Inference Article Early warning of complex climate risk with integrated artificial intelligence Reichstein, M., Benson, V., Blunk, J., Camps-Valls, G., Creutzig, F., Fearnley, C. J., Han, B., Kornhuber, K., Rahaman, N., Schölkopf, B., et al. Nature Communications, 16(1), March 2025 (Published) DOI BibTeX

Empirical Inference Conference Paper Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models Vetter, J., Gloeckler, M., Gedon, D., Macke, J. H. Advances in Neural Information Processing Systems 38 (NeurIPS 2025), 39th Annual Conference on Neural Information Processing Systems, December 2025 (Accepted) arXiv BibTeX

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