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iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects



Phillip Lippe , Sara Magliacane , Sindy Löwe , Yuki M. Asano , Taco Cohen , Efstratios Gavves


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Factored Adaptation for Non-Stationary Reinforcement Learning



Fan Feng , Biwei Huang , Kun Zhang , Sara Magliacane

* 20 pages, 11 figures 

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CITRIS: Causal Identifiability from Temporal Intervened Sequences



Phillip Lippe , Sara Magliacane , Sindy Löwe , Yuki M. Asano , Taco Cohen , Efstratios Gavves

* 47 pages 

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AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning



Biwei Huang , Fan Feng , Chaochao Lu , Sara Magliacane , Kun Zhang


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Active Structure Learning of Causal DAGs via Directed Clique Tree



Chandler Squires , Sara Magliacane , Kristjan Greenewald , Dmitriy Katz , Murat Kocaoglu , Karthikeyan Shanmugam

* NeurIPS 2020 

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Verifiably Safe Exploration for End-to-End Reinforcement Learning



Nathan Hunt , Nathan Fulton , Sara Magliacane , Nghia Hoang , Subhro Das , Armando Solar-Lezama


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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

* Camera-ready version, to be published in the proceedings of Neural Information Processing Systems 2018 (NIPS*2018) 

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An Upper Bound for Random Measurement Error in Causal Discovery



Tineke Blom , Anna Klimovskaia , Sara Magliacane , Joris M. Mooij

* Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence, 2018 
* Published in Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence (UAI-18) 

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