Magliacane, Sara

29 publications

CLeaR 2025 Combining Causal Models for More Accurate Abstractions of Neural Networks Theodora-Mara Pîslar, Sara Magliacane, Atticus Geiger

NeurIPS 2025 Learning Interactive World Model for Object-Centric Reinforcement Learning Fan Feng, Phillip Lippe, Sara Magliacane

ICLRW 2025 Learning to Defer for Causal Discovery with Imperfect Experts Oscar Clivio, Divyat Mahajan, Perouz Taslakian, Sara Magliacane, Ioannis Mitliagkas, Valentina Zantedeschi, Alexandre Drouin

AISTATS 2025 SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation with an Unknown Graph Mátyás Schubert, Tom Claassen, Sara Magliacane

NeurIPS 2025 Sample-Efficient Learning of Concepts with Theoretical Guarantees: From Data to Concepts Without Interventions Hidde Fokkema, Tim van Erven, Sara Magliacane

ICML 2024 A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius Von Kügelgen, Francesco Locatello, Sara Magliacane

ICML 2024 Amortized Equation Discovery in Hybrid Dynamical Systems Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Stratis Gavves

UAI 2024 Learning Causal Abstractions of Linear Structural Causal Models Riccardo Massidda, Sara Magliacane, Davide Bacciu

ICLR 2024 Multi-View Causal Representation Learning with Partial Observability Dingling Yao, Danru Xu, Sebastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello

CLeaR 2024 Towards the Reusability and Compositionality of Causal Representations Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane

NeurIPSW 2023 A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane

UAI 2023 BISCUIT: Causal Representation Learning from Binary Interactions Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves

ICLR 2023 Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves

ICML 2023 Graph Switching Dynamical Systems Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves

NeurIPSW 2023 Hierarchical Causal Representation Learning Angelos Nalmpantis, Phillip Lippe, Sara Magliacane

NeurIPS 2023 Learning Dynamic Attribute-Factored World Models for Efficient Multi-Object Reinforcement Learning Fan Feng, Sara Magliacane

NeurIPS 2023 Modulated Neural ODEs Ilze Amanda Auzina, Çağatay Yıldız, Sara Magliacane, Matthias Bethge, Efstratios Gavves

NeurIPSW 2023 Multi-View Causal Representation Learning with Partial Observability Dingling Yao, Danru Xu, Sebastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello

NeurIPSW 2023 Towards the Reusability and Compositionality of Causal Representations Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane

ICLR 2022 AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang

ICML 2022 CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Stratis Gavves

ICLRW 2022 CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves

NeurIPS 2022 Factored Adaptation for Non-Stationary Reinforcement Learning Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane

NeurIPS 2020 Active Structure Learning of Causal DAGs via Directed Clique Trees Chandler Squires, Sara Magliacane, Kristjan Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

JMLR 2020 Joint Causal Inference from Multiple Contexts Joris M. Mooij, Sara Magliacane, Tom Claassen

NeurIPS 2019 Sample Efficient Active Learning of Causal Trees Kristjan Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adsera, Guy Bresler

UAI 2018 Causal Discovery in the Presence of Measurement Error Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij

NeurIPS 2018 Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij

NeurIPS 2016 Ancestral Causal Inference Sara Magliacane, Tom Claassen, Joris M. Mooij