Search results
Results: 19
Number of items: 19
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Pîslar, T.-M., Magliacane, S., & Geiger, A. (2025). Combining Causal Models for More Accurate Abstractions of Neural Networks. Proceedings of Machine Learning Research, 275, 114-138. https://proceedings.mlr.press/v275/pislar25a.html -
van Geloven, N., Keogh, R. H., van Amsterdam, W., Cinà, G., Krijthe, J. H., Peek, N., Luijken, K., Magliacane, S., Morzywołek, P., van Ommen, T., Putter, H., Sperrin, M., Wang, J., Weir, D. L., & Didelez, V. (2025). The Risks of Risk Assessment: Causal Blind Spots When Using Prediction Models for Treatment Decisions. Annals of Internal Medicine, 178(9), 1326-1333. https://doi.org/10.7326/ANNALS-24-00279
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Liu, Y., Magliacane, S., Kofinas, M., & Gavves, E. (2024). Amortized Equation Discovery in Hybrid Dynamical Systems. Proceedings of Machine Learning Research, 235, 31645-31668. https://proceedings.mlr.press/v235/liu24at.html
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Meimetis, N., Pullen, K. M., Zhu, D. Y., Nilsson, A., Hoang, T. N., Magliacane, S., & Lauffenburger, D. A. (2024). AutoTransOP: translating omics signatures without orthologue requirements using deep learning. Npj Systems Biology and Applications, 10, Article 13. https://doi.org/10.1038/s41540-024-00341-9
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Luijken, K., Morzywołek, P., van Amsterdam, W., Cinà, G., Hoogland, J., Keogh, R., Krijthe, J. H., Magliacane, S., van Ommen, T., Peek, N., Putter, H., van Smeden, M., Sperrin, M., Wang, J., Weir, D. L., Didelez, V., & van Geloven, N. (2024). Risk‐Based Decision Making: Estimands for Sequential Prediction Under Interventions. Biometrical Journal, 66(8), Article e70011. https://doi.org/10.1002/bimj.70011
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Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., & Magliacane, S. (2024). A Sparsity Principle for Partially Observable Causal Representation Learning. Proceedings of Machine Learning Research, 235, 55389-55433. https://proceedings.mlr.press/v235/xu24ac.html
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Liu, Y., Magliacane, S., Kofinas, M., & Gavves, E. (2023). Graph switching dynamical systems. Proceedings of Machine Learning Research, 202, 21867-21883. https://proceedings.mlr.press/v202/liu23z.html
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Lippe, P., Magliacane, S., Löwe, S., Asano, Y. M., Cohen, T., & Gavves, E. (2023). BISCUIT: Causal Representation Learning from Binary Interactions. Proceedings of Machine Learning Research, 216, 1263-1273. https://proceedings.mlr.press/v216/lippe23a.html
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Feng, F., Huang, B., Magliacane, S., & Zhang, K. (2023). Factored Adaptation for Non-Stationary Reinforcement Learning. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 41, pp. 31957-31971). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2203.16582
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