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Andrew Jesson

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DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design

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Dec 07, 2023
Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab

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BatchGFN: Generative Flow Networks for Batch Active Learning

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Jun 26, 2023
Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal

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ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages

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Jun 12, 2023
Andrew Jesson, Chris Lu, Gunshi Gupta, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

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B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding

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Apr 20, 2023
Miruna Oprescu, Jacob Dorn, Marah Ghoummaid, Andrew Jesson, Nathan Kallus, Uri Shalit

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Differentiable Multi-Target Causal Bayesian Experimental Design

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Feb 21, 2023
Yashas Annadani, Panagiotis Tigas, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

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

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

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Interventions, Where and How? Experimental Design for Causal Models at Scale

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Mar 03, 2022
Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer

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

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

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Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific

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Nov 03, 2021
Andrew Jesson, Peter Manshausen, Alyson Douglas, Duncan Watson-Parris, Yarin Gal, Philip Stier

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