Sara Magliacane

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 38

Top Topics

Coreference Resolution

Ordinary Differential Equations

Reinforcement Learning

Top Venues

Publications

Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves
Amortized Equation Discovery in Hybrid Dynamical Systems. CoRR (2024)
Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
Multi-View Causal Representation Learning with Partial Observability. ICLR (2024)
Riccardo Massidda, Sara Magliacane, Davide Bacciu
Learning Causal Abstractions of Linear Structural Causal Models. CoRR (2024)
Kun Zhang, Ilya Shpitser, Sara Magliacane, Davide Bacciu, Fei Wu, Changshui Zhang, Peter Spirtes
IEEE Transactions on Neural Networks and Learning Systems Special Issue on Causal Discovery and Causality-Inspired Machine Learning. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane
A Sparsity Principle for Partially Observable Causal Representation Learning. CoRR (2024)
Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane
Towards the Reusability and Compositionality of Causal Representations. CLeaR (2024)
Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane
Towards the Reusability and Compositionality of Causal Representations. CoRR (2024)
Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
Multi-View Causal Representation Learning with Partial Observability. CoRR (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
BISCUIT: Causal Representation Learning from Binary Interactions. UAI (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems. ICLR (2023)
Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves
Invariant Neural Ordinary Differential Equations. CoRR (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
BISCUIT: Causal Representation Learning from Binary Interactions. CoRR (2023)
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves
Graph Switching Dynamical Systems. ICML (2023)
Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves
Modulated Neural ODEs. NeurIPS (2023)
Fan Feng, Sara Magliacane
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. CoRR (2023)
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves
Graph Switching Dynamical Systems. CoRR (2023)
Fan Feng, Sara Magliacane
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. NeurIPS (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
CITRIS: Causal Identifiability from Temporal Intervened Sequences. CoRR (2022)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects. CoRR (2022)
Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane
Factored Adaptation for Non-Stationary Reinforcement Learning. NeurIPS (2022)
Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. ICLR (2022)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Stratis Gavves
CITRIS: Causal Identifiability from Temporal Intervened Sequences. ICML (2022)
Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane
Factored Adaptation for Non-Stationary Reinforcement Learning. CoRR (2022)
Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. CoRR (2021)
Nathan Hunt, Nathan Fulton, Sara Magliacane, Trong Nghia Hoang, Subhro Das, Armando Solar-Lezama
Verifiably safe exploration for end-to-end reinforcement learning. HSCC (2021)
Xue Li, Sara Magliacane, Paul Groth
The Challenges of Cross-Document Coreference Resolution for Email. K-CAP (2021)
Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
Active Structure Learning of Causal DAGs via Directed Clique Trees. NeurIPS (2020)
Joris M. Mooij, Sara Magliacane, Tom Claassen
Joint Causal Inference from Multiple Contexts. J. Mach. Learn. Res. 21 (2020)
Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR (2020)
Nathan Hunt, Nathan Fulton, Sara Magliacane, Nghia Hoang, Subhro Das, Armando Solar-Lezama
Verifiably Safe Exploration for End-to-End Reinforcement Learning. CoRR (2020)
Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler
Sample Efficient Active Learning of Causal Trees. NeurIPS (2019)
Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions. NeurIPS (2018)
Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij
An Upper Bound for Random Measurement Error in Causal Discovery. CoRR (2018)
Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij
Causal Discovery in the Presence of Measurement Error. UAI (2018)
Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
Causal Transfer Learning. CoRR (2017)
Sara Magliacane, Tom Claassen, Joris M. Mooij
Joint Causal Inference on Observational and Experimental Datasets. CoRR (2016)
Sara Magliacane, Tom Claassen, Joris M. Mooij
Ancestral Causal Inference. NIPS (2016)
Sara Magliacane, Tom Claassen, Joris M. Mooij
Ancestral Causal Inference. CoRR (2016)
Sara Magliacane, Philip Stutz, Paul Groth, Abraham Bernstein
FoxPSL: An Extended and Scalable PSL Implementation. AAAI Spring Symposia (2015)
Sara Magliacane, Philip Stutz, Paul Groth, Abraham Bernstein
foxPSL: A Fast, Optimized and eXtended PSL implementation. Int. J. Approx. Reason. 67 (2015)
Tom De Nies, Sara Magliacane, Ruben Verborgh, Sam Coppens, Paul Groth, Erik Mannens, Rik Van de Walle
Git2PROV: Exposing Version Control System Content as W3C PROV. ISWC (Posters & Demos) (2013)
Sara Magliacane, Paul Groth
Repurposing Benchmark Corpora for Reconstructing Provenance. SePublica (2013)
Sara Magliacane, Alessandro Bozzon, Emanuele Della Valle
Efficient Execution of Top-K SPARQL Queries. ISWC (1) (2012)
Rinke Hoekstra, Sara Magliacane, Laurens Rietveld, Gerben de Vries, Adianto Wibisono, Stefan Schlobach
Hubble: Linked Data Hub for Clinical Decision Support. ESWC (Satellite Events) (2012)
Sara Magliacane, Paul Groth
Towards Reconstructing the Provenance of Clinical Guidelines. SWAT4LS (2012)
Paul Groth, Yolanda Gil, Sara Magliacane
Automatic Metadata Annotation through Reconstructing Provenance. SWPM@ESWC (2012)
Julie M. Birkholz, Shenghui Wang, Paul Groth, Sara Magliacane
Who Are We Talking About? Identifying Scientific Populations Online. CSWS (2012)
Sara Magliacane
Reconstructing Provenance. ISWC (2) (2012)