Sara Magliacane

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Tom ClaassenRadboud University NijmegenVerified email at cs.ru.nl
Joris M. MooijProfessor in Mathematical Statistics, Korteweg-de Vries Institute, University of Amsterdam (NL)Verified email at uva.nl
Efstratios GavvesAssociate Professor at University of AmsterdamVerified email at uva.nl
Phillip LippeGoogle DeepMindVerified email at google.com
Yuki M. AsanoFull Professor, Head of FunAI Lab, University of Technology NurembergVerified email at utn.de
Paul GrothProfessor, INDE Lab, University of AmsterdamVerified email at uva.nl
Taco CohenQualcomm AI ResearchVerified email at qti.qualcomm.com
Thijs van OmmenAssistant Professor at Utrecht UniversityVerified email at uu.nl
Sindy LöweCuspAIVerified email at cusp.ai
Philip VersteegPhD Student, University of AmsterdamVerified email at uva.nl
Stephan BongersPostdoctoral Researcher, Delft University of TechnologyVerified email at uva.nl
Trong Nghia HoangAssistant Professor, Washington State UniversityVerified email at wsu.edu
Fan FengCity University of Hong KongVerified email at my.cityu.edu.hk
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at cmu.edu
Emanuele Della VallePolitecnico di MilanoVerified email at polimi.it
Alessandro BozzonProfessor Human-Centered AI, Delft University of TechnologyVerified email at tudelft.nl
Biwei HuangUCSDVerified email at andrew.cmu.edu
Kristjan GreenewaldResearch Scientist, MIT-IBM Watson AI Lab, IBM ResearchVerified email at ibm.com
Karthikeyan ShanmugamResearch Scientist, Google Research IndiaVerified email at google.com
Murat KocaogluAssistant Professor, School of ECE, Purdue UniversityVerified email at purdue.edu

Sara Magliacane

University of Amsterdam

Verified email at uva.nl - Homepage

Causality Causal Discovery Statistical relational learning Probabilistic logics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Joint causal inference from multiple contexts JM Mooij, S Magliacane, T Claassen JMLR, 2020	278	2020
Domain adaptation by using causal inference to predict invariant conditional distributions S Magliacane, T van Ommen, T Claassen, S Bongers, P Versteeg, ... NeurIPS 2018, 2017	276	2017
Citris: Causal identifiability from temporal intervened sequences P Lippe, S Magliacane, S Löwe, YM Asano, T Cohen, S Gavves International Conference on Machine Learning, 13557-13603, 2022	114	2022
Adarl: What, where, and how to adapt in transfer reinforcement learning B Huang, F Feng, C Lu, S Magliacane, K Zhang ICLR 2022, 2021	75	2021
Git2PROV: Exposing Version Control System Content as W3C PROV. T De Nies, S Magliacane, R Verborgh, S Coppens, P Groth, E Mannens, ... ISWC (Posters & Demos), 125-128, 2013	72	2013
Ancestral Causal Inference S Magliacane, T Claassen, JM Mooij NIPS 2016, 2016	71	2016
Causal representation learning for instantaneous and temporal effects in interactive systems P Lippe, S Magliacane, S Löwe, YM Asano, T Cohen, E Gavves ICLR 2022, 2022	65*	2022
Verifiably safe exploration for end-to-end reinforcement learning N Hunt, N Fulton, S Magliacane, TN Hoang, S Das, A Solar-Lezama Proceedings of the 24th International Conference on Hybrid Systems …, 2021	60	2021
Efficient Execution of Top-K SPARQL Queries S Magliacane, A Bozzon, E Della Valle ISWC 2012, 2012	60	2012
Sample efficient active learning of causal trees K Greenewald, D Katz, K Shanmugam, S Magliacane, M Kocaoglu, ... Advances in Neural Information Processing Systems 32, 2019	48	2019
Factored adaptation for non-stationary reinforcement learning F Feng, B Huang, K Zhang, S Magliacane NeurIPS 2021, 2022	43	2022
Active structure learning of causal DAGs via directed clique trees C Squires, S Magliacane, K Greenewald, D Katz, M Kocaoglu, ... Advances in Neural Information Processing Systems 33, 21500-21511, 2020	39	2020
Reconstructing Provenance S Magliacane ISWC 2012, 2012	32	2012
Biscuit: Causal representation learning from binary interactions P Lippe, S Magliacane, S Löwe, YM Asano, T Cohen, E Gavves Uncertainty in Artificial Intelligence, 1263-1273, 2023	31	2023
Multi-view causal representation learning with partial observability D Yao, D Xu, S Lachapelle, S Magliacane, P Taslakian, G Martius, ... ICLR 2024 Spotlight, 2024	30	2024
Automatic Metadata Annotation through Reconstructing Provenance P Groth, Y Gil, S Magliacane Third International Workshop on the role of Semantic Web in Provenance …, 2012	22	2012
An Upper Bound for Random Measurement Error in Causal Discovery T Blom, A Klimovskaia, S Magliacane, JM Mooij Uncertainty in Artificial Intelligence, 2018	14	2018
Learning dynamic attribute-factored world models for efficient multi-object reinforcement learning F Feng, S Magliacane Advances in Neural Information Processing Systems 36, 19117-19144, 2023	12	2023
A Sparsity Principle for Partially Observable Causal Representation Learning D Xu, D Yao, S Lachapelle, P Taslakian, J von Kügelgen, F Locatello, ... ICML 2024, 2024	11	2024
Intervention Design for Causal Representation Learning P Lippe, S Magliacane, S Löwe, YM Asano, T Cohen, E Gavves UAI 2022 Workshop on Causal Representation Learning, 2022	11	2022

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