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ORCIDSara Magliacane
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2020 – today
- 2024
[j3]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): 4899-4901 (2024)- [c28]Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane:
Towards the Reusability and Compositionality of Causal Representations. CLeaR 2024: 296-324 - [c27]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 - [c26]Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Stratis Gavves:
Amortized Equation Discovery in Hybrid Dynamical Systems. ICML 2024 - [c25]Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane:
A Sparsity Principle for Partially Observable Causal Representation Learning. ICML 2024 - [i19]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 abs/2403.08335 (2024) - [i18]Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane:
Towards the Reusability and Compositionality of Causal Representations. CoRR abs/2403.09830 (2024) - [i17]Riccardo Massidda, Sara Magliacane, Davide Bacciu:
Learning Causal Abstractions of Linear Structural Causal Models. CoRR abs/2406.00394 (2024) - [i16]Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves:
Amortized Equation Discovery in Hybrid Dynamical Systems. CoRR abs/2406.03818 (2024) - 2023
- [c24]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 - [c23]Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves:
Graph Switching Dynamical Systems. ICML 2023: 21867-21883 - [c22]Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves:
Modulated Neural ODEs. NeurIPS 2023 - [c21]Fan Feng, Sara Magliacane:
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. NeurIPS 2023 - [c20]Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves:
BISCUIT: Causal Representation Learning from Binary Interactions. UAI 2023: 1263-1273 - [i15]Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves:
Invariant Neural Ordinary Differential Equations. CoRR abs/2302.13262 (2023) - [i14]Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves:
Graph Switching Dynamical Systems. CoRR abs/2306.00370 (2023) - [i13]Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves:
BISCUIT: Causal Representation Learning from Binary Interactions. CoRR abs/2306.09643 (2023) - [i12]Fan Feng, Sara Magliacane:
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. CoRR abs/2307.09205 (2023) - [i11]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 abs/2311.04056 (2023) - 2022
- [c19]Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang:
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. ICLR 2022 - [c18]Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Stratis Gavves:
CITRIS: Causal Identifiability from Temporal Intervened Sequences. ICML 2022: 13557-13603 - [c17]Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane:
Factored Adaptation for Non-Stationary Reinforcement Learning. NeurIPS 2022 - [i10]Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves:
CITRIS: Causal Identifiability from Temporal Intervened Sequences. CoRR abs/2202.03169 (2022) - [i9]Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane:
Factored Adaptation for Non-Stationary Reinforcement Learning. CoRR abs/2203.16582 (2022) - [i8]Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves:
iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects. CoRR abs/2206.06169 (2022) - 2021
- [c16]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: 14:1-14:11 - [c15]Xue Li, Sara Magliacane, Paul Groth:
The Challenges of Cross-Document Coreference Resolution for Email. K-CAP 2021: 273-276 - [i7]Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang:
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. CoRR abs/2107.02729 (2021) - 2020
- [j2]Joris M. Mooij, Sara Magliacane, Tom Claassen:
Joint Causal Inference from Multiple Contexts. J. Mach. Learn. Res. 21: 99:1-99:108 (2020) - [c14]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 - [i6]Nathan Hunt, Nathan Fulton, Sara Magliacane, Nghia Hoang, Subhro Das, Armando Solar-Lezama:
Verifiably Safe Exploration for End-to-End Reinforcement Learning. CoRR abs/2007.01223 (2020) - [i5]Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam:
Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR abs/2011.00641 (2020)
2010 – 2019
- 2019
- [c13]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: 14279-14289 - 2018
- [c12]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: 10869-10879 - [c11]Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij:
Causal Discovery in the Presence of Measurement Error. UAI 2018: 570-579 - [i4]Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij:
An Upper Bound for Random Measurement Error in Causal Discovery. CoRR abs/1810.07973 (2018) - 2017
- [i3]Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij:
Causal Transfer Learning. CoRR abs/1707.06422 (2017) - 2016
- [c10]Sara Magliacane, Tom Claassen, Joris M. Mooij:
Ancestral Causal Inference. NIPS 2016: 4466-4474 - [i2]Sara Magliacane, Tom Claassen, Joris M. Mooij:
Ancestral Causal Inference. CoRR abs/1606.07035 (2016) - [i1]Sara Magliacane, Tom Claassen, Joris M. Mooij:
Joint Causal Inference on Observational and Experimental Datasets. CoRR abs/1611.10351 (2016) - 2015
- [j1]Sara Magliacane, Philip Stutz, Paul Groth, Abraham Bernstein:
foxPSL: A Fast, Optimized and eXtended PSL implementation. Int. J. Approx. Reason. 67: 111-121 (2015) - [c9]Sara Magliacane, Philip Stutz, Paul Groth, Abraham Bernstein:
FoxPSL: An Extended and Scalable PSL Implementation. AAAI Spring Symposia 2015 - 2013
- [c8]Sara Magliacane, Paul Groth:
Repurposing Benchmark Corpora for Reconstructing Provenance. SePublica 2013: 39-50 - [c7]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: 125-128 - 2012
- [c6]Julie M. Birkholz, Shenghui Wang, Paul Groth, Sara Magliacane:
Who Are We Talking About? Identifying Scientific Populations Online. CSWS 2012: 237-250 - [c5]Paul Groth, Yolanda Gil, Sara Magliacane:
Automatic Metadata Annotation through Reconstructing Provenance. SWPM@ESWC 2012 - [c4]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: 458-462 - [c3]Sara Magliacane, Alessandro Bozzon, Emanuele Della Valle:
Efficient Execution of Top-K SPARQL Queries. ISWC (1) 2012: 344-360 - [c2]Sara Magliacane:
Reconstructing Provenance. ISWC (2) 2012: 399-406 - [c1]Sara Magliacane, Paul Groth:
Towards Reconstructing the Provenance of Clinical Guidelines. SWAT4LS 2012 - [p1]Alessandro Bozzon, Emanuele Della Valle, Sara Magliacane:
Extending SPARQL Algebra to Support Efficient Evaluation of Top-K SPARQL Queries. SeCO Book 2012: 143-156
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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