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5373 Publications
2023 | Published | Conference Paper | IST-REx-ID: 14084 | 
Harris, D. G., & Kolmogorov, V. (2023). Parameter estimation for Gibbs distributions. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2023.72
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14085 |
Goranci, G., & Henzinger, M. (2023). Efficient data structures for incremental exact and approximate maximum flow. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2023.69
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2023 | Published | Conference Paper | IST-REx-ID: 14086 |
Henzinger, M., Liu, P., Vondrák, J., & Zheng, D. W. (2023). Faster submodular maximization for several classes of matroids. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2023.74
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14105 |
Sinha, S., Gehler, P., Locatello, F., & Schiele, B. (2023). TeST: Test-time Self-Training under distribution shift. In 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, HI, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/wacv56688.2023.00278
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14192 |
Lampart, J., Mitrouskas, D. J., & Mysliwy, K. (2023). On the global minimum of the energy–momentum relation for the polaron. Mathematical Physics, Analysis and Geometry. Springer Nature. https://doi.org/10.1007/s11040-023-09460-x
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14207 |
Löwe, S., Lippe, P., Locatello, F., & Welling, M. (n.d.). Rotating features for object discovery. arXiv. https://doi.org/10.48550/arXiv.2306.00600
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2023 | Published | Conference Paper | IST-REx-ID: 14208 |
Zhu, Z., Liu, F., Chrysos, G. G., Locatello, F., & Cevher, V. (2023). Benign overfitting in deep neural networks under lazy training. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 43105–43128). Honolulu, Hawaii, United States: ML Research Press.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14209 |
Burg, M. F., Wenzel, F., Zietlow, D., Horn, M., Makansi, O., Locatello, F., & Russell, C. (n.d.). A data augmentation perspective on diffusion models and retrieval. arXiv. https://doi.org/10.48550/arXiv.2304.10253
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14210 |
Fumero, M., Wenzel, F., Zancato, L., Achille, A., Rodolà, E., Soatto, S., … Locatello, F. (n.d.). Leveraging sparse and shared feature activations for disentangled representation learning. arXiv. https://doi.org/10.48550/arXiv.2304.07939
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14211 |
Montagna, F., Noceti, N., Rosasco, L., Zhang, K., & Locatello, F. (2023). Causal discovery with score matching on additive models with arbitrary noise. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.
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2023 | Published | Conference Paper | IST-REx-ID: 14212 |
Montagna, F., Noceti, N., Rosasco, L., Zhang, K., & Locatello, F. (2023). Scalable causal discovery with score matching. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14214 |
Liu, Y., Alahi, A., Russell, C., Horn, M., Zietlow, D., Schölkopf, B., & Locatello, F. (2023). Causal triplet: An open challenge for intervention-centric causal representation learning. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.
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2023 | Published | Conference Paper | IST-REx-ID: 14217 |
Moschella, L., Maiorca, V., Fumero, M., Norelli, A., Locatello, F., & Rodolà, E. (2023). Relative representations enable zero-shot latent space communication. In The 11th International Conference on Learning Representations. Kigali, Rwanda.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14218 |
Seitzer, M., Horn, M., Zadaianchuk, A., Zietlow, D., Xiao, T., Carl-Johann Simon-Gabriel, C.-J. S.-G., … Locatello, F. (2023). Bridging the gap to real-world object-centric learning. In The 11th International Conference on Learning Representations. Kigali, Rwanda.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14219 |
Zadaianchuk, A., Kleindessner, M., Zhu, Y., Locatello, F., & Brox, T. (2023). Unsupervised semantic segmentation with self-supervised object-centric representations. In The 11th International Conference on Learning Representations. Kigali, Rwanda.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14222 |
Tangemann, M., Schneider, S., Kügelgen, J. von, Locatello, F., Gehler, P., Brox, T., … Schölkopf, B. (2023). Unsupervised object learning via common fate. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14238 |
Kranabetter, L., Kristensen, H. H., Ghazaryan, A., Schouder, C. A., Chatterley, A. S., Janssen, P., … Stapelfeldt, H. (2023). Nonadiabatic laser-induced alignment dynamics of molecules on a surface. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.131.053201
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14239 |
Mauri, M., & Shinder, E. (2023). Homological Bondal-Orlov localization conjecture for rational singularities. Forum of Mathematics, Sigma. Cambridge University Press. https://doi.org/10.1017/fms.2023.65
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14240 |
Jeschke, S., & Wojtan, C. (2023). Generalizing shallow water simulations with dispersive surface waves. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3592098
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2023 | Published | Conference Paper | IST-REx-ID: 14241 |
Tojo, K., Shamir, A., Bickel, B., & Umetani, N. (2023). Stealth shaper: Reflectivity optimization as surface stylization. In SIGGRAPH 2023 Conference Proceedings. Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3588432.3591542
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