Dr. S. (Sara) Magliacane
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute
Bezoekadres
- Science Park 904
Postadres
-
Postbus 94323
1090 GH Amsterdam
Contactgegevens
-
Publicaties
2026
- Schubert, M., Claassen, T., & Magliacane, S. (in press). Local Causal Discovery for Statistically Efficient Causal Inference. In The 29th International Conference on Artificial Intelligence and Statistics https://openreview.net/forum?id=FlWl20PFd7
2025
- 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.
- Schubert, M., Claassen, T., & Magliacane, S. (2025). SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph. Proceedings of Machine Learning Research, 258, 3340-3348. https://proceedings.mlr.press/v258/schubert25a.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
2024
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 [details]- 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 [details]
- 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 [details]
- 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.
2023
- Auzina, I. A., Yildiz, C., Magliacane, S., Bethge, M., & Gavves, E. (2023). Modulated Neural ODEs. In 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://proceedings.neurips.cc/paper_files/paper/2023/hash/8bc74514d554a90c996576f6c373f5f3-Abstract-Conference.html
- Feng, F., & Magliacane, S. (2023). Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. In A. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023 (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation.
- 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 [details]
- Lippe, P., Magliacane, S., Löwe, S., Asano, Y. M., Cohen, T., & Gavves, E. (2023). Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems. In The Eleventh International Conference on Learning Representations https://openreview.net/forum?id=itZ6ggvMnzS
- 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 [details]
2022
- Lippe, P., Magliacane, S., Löwe, S., Asano, Y. M., Cohen, T., & Gavves, E. (2022). CITRIS: Causal Identifiability from Temporal Intervened Sequences. Proceedings of Machine Learning Research, 162, 13557-13603. https://proceedings.mlr.press/v162/lippe22a.html [details]
2021
- Hunt, N., Fulton, N., Magliacane, S., Hoang, T. N., Das, S., & Solar-Lezama, A. (2021). Verifiably Safe Exploration for End-to-End Reinforcement Learning. In HSCC2021: proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (part of CPS-IoT Week) : May 19-21, 2021, Nashville, TN, USA Article 14 The Association for Computing Machinery. https://doi.org/10.1145/3447928.3456653 [details]
- Li, X., Magliacane, S., & Groth, P. (2021). The Challenges of Cross-Document Coreference Resolution in Email. In K-CAP '21: Proceedings of the 11th Knowledge Capture Conference : December 2-3, 2021 : virtual event, USA (pp. 273-276). Association for Computing Machinery. https://doi.org/10.1145/3460210.3493573 [details]
2020
- Mooij, J. M., Magliacane, S., & Claassen, T. (2020). Joint Causal Inference from Multiple Contexts. Journal of Machine Learning Research, 21(99), Article 99. https://www.jmlr.org/papers/v21/ [details]
2019
- Magliacane, S., van Ommen, T., Claassen, T., Bongers, S., Versteeg, P., & Mooij, J. M. (2019). Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems 2018: Montreal, Canada, 3-8 December 2018 (Vol. 15, pp. 10846-10856). (Advances in Neural Information Processing Systems; Vol. 31). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/8282-domain-adaptation-by-using-causal-inference-to-predict-invariant-conditional-distributions [details]
2018
- Blom, T., Klimovskaia, A., Magliacane, S., & Mooij, J. M. (2018). An Upper Bound for Random Measurement Error in Causal Discovery. In A. Globerson, & R. Silva (Eds.), Uncertainty in Artificial Intelligence: proceedings of the Thirty-Fourth Concerence (2018) : August 6-10, 2018, Monterey, California, USA (pp. 570-579). AUAI Press. http://auai.org/uai2018/proceedings/papers/208.pdf [details]
2017
- Magliacane, S., Claassen, T., & Mooij, J. (2017). Ancestral Causal Inference. In D. D. Lee, U. von Luxburg, R. Garnett, M. Sugiyama, & I. Guyon (Eds.), 30th Annual Conference on Neural Information Processing Systems 2016: Barcelona, Spain, 5-10 December 2016 (Vol. 7, pp. 4473-4481). (Advances in Neural Information Processing Systems; Vol. 29). Curran Associates. http://papers.nips.cc/paper/6266-ancestral-causal-inference [details]
2015
- Hoekstra, R., Magliacane, S., Rietveld, L., de Vries, G., Wibisono, A., & Schlobach, S. (2015). Hubble: Linked Data Hub for Clinical Decision Support. In E. Simperl, B. Norton, D. Mladenic, E. Della Valle, I. Fundulaki, A. Passant, & R. Troncy (Eds.), The Semantic Web: ESWC 2012 Satellite Events: ESWC 2012 Satellite Events, Heraklion, Crete, Greece, May 27-31, 2012 : revised selected papers (pp. 458-462). (Lecture Notes in Computer Science; Vol. 7540). Springer. https://doi.org/10.1007/978-3-662-46641-4_45 [details]
2023
- 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 [details]
2024
- Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., von Kügelgen, J., & Locatello, F. (2024). MULTI-VIEW CAUSAL REPRESENTATION LEARNING WITH PARTIAL OBSERVABILITY. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria. https://openreview.net/forum?id=OGtnhKQJms
2022
- Huang, B., Feng, F., Lu, C., Magliacane, S., & Zhang, K. (2022). ADARL: WHAT, WHERE, AND HOW TO ADAPT IN TRANSFER REINFORCEMENT LEARNING. Paper presented at 10th International Conference on Learning Representations, ICLR 2022, Virtual, Online.
2020
- Squires, C., Magliacane, S., Greenewald, K., Katz, D., Kocaoglu, M., & Shanmugam, K. (2020). Active structure learning of causal DAGs via directed clique trees. Poster session presented at 34th Conference on Neural Information Processing Systems, NeurIPS 2020, Virtual, Online.
Andere
- van Benthem, J. (organiser), ten Cate, B. (organiser), van Harmelen, F. (organiser), Hornischer, L. (organiser), Icard, T. (organiser) & Magliacane, S. (organiser) (2024). Logic and AI, Research Project and Workshop, Amsterdam (organising a conference, workshop, ...).
This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list. -
Nevenwerkzaamheden
Geen nevenwerkzaamheden
Liu, Y., Magliacane, S., Kofinas, M., & Gavves, E. (2024). Amortized Equation Discovery in Hybrid Dynamical Systems. Proceedings of Machine Learning Research, 235, 31645-31668.