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 LippePhD Student, University of AmsterdamVerified email at uva.nl
Paul GrothProfessor, INDE Lab, University of AmsterdamVerified email at uva.nl
Yuki M. AsanoFull Professor, Head of FunAI Lab, University of Technology NurembergVerified email at utn.de
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
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
Trong Nghia HoangAssistant Professor, Washington State UniversityVerified email at wsu.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


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Joint causal inference from multiple contexts JM Mooij, S Magliacane, T Claassen JMLR, 2020	262	2020
Domain adaptation by using causal inference to predict invariant conditional distributions S Magliacane, T van Ommen, T Claassen, S Bongers, P Versteeg, ... arXiv preprint arXiv:1707.06422, 2017	262	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	103	2022
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	71	2013
Adarl: What, where, and how to adapt in transfer reinforcement learning B Huang, F Feng, C Lu, S Magliacane, K Zhang ICLR 2022, 2021	67	2021
Ancestral Causal Inference S Magliacane, T Claassen, JM Mooij NIPS 2016, 2016	66	2016
Efficient Execution of Top-K SPARQL Queries S Magliacane, A Bozzon, E Della Valle ISWC 2012, 2012	58	2012
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	56*	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	54	2021
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
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
Factored adaptation for non-stationary reinforcement learning F Feng, B Huang, K Zhang, S Magliacane NeurIPS 2021, 2022	37	2022
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	28	2023
Multi-view causal representation learning with partial observability D Yao, D Xu, S Lachapelle, S Magliacane, P Taslakian, G Martius, ... ICLR 2024 Spotlight, 2023	22	2023
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	12	2018
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	10	2022
Learning dynamic attribute-factored world models for efficient multi-object reinforcement learning F Feng, S Magliacane Advances in Neural Information Processing Systems 36, 2024	9	2024
foxPSL: A Fast, Optimized and eXtended PSL implementation S Magliacane, P Stutz, P Groth, A Bernstein International Journal of Approximate Reasoning 67, 111-121, 2015	9	2015

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