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Reinforcement Learning with a Terminator


May 30, 2022
Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal


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Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions


Apr 26, 2022
Andrew Jesson, Alyson Douglas, Peter Manshausen, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit

* 22 pages 

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Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data


Nov 03, 2021
Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal

* 24 pages, 8 Figures, 5 tables, NeurIPS 2021 

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On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning


Oct 13, 2021
Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit


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Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding


Mar 08, 2021
Andrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit

* 18 pages, 5 figures, In review 

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On Calibration and Out-of-domain Generalization


Feb 20, 2021
Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit

* 24 pages, 6 figures 

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Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression


Feb 16, 2021
Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet


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Using Deep Networks for Scientific Discovery in Physiological Signals


Aug 25, 2020
Tom Beer, Bar Eini-Porat, Sebastian Goodfellow, Danny Eytan, Uri Shalit

* 2020 Machine Learning for Healthcare Conference 

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Identifying Causal Effect Inference Failure with Uncertainty-Aware Models


Jul 01, 2020
Andrew Jesson, Sören Mindermann, Uri Shalit, Yarin Gal


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