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Tom Rainforth

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Incorporating Unlabelled Data into Bayesian Neural Networks

Apr 04, 2023
Mrinank Sharma, Tom Rainforth, Yee Whye Teh, Vincent Fortuin

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Modern Bayesian Experimental Design

Feb 28, 2023
Tom Rainforth, Adam Foster, Desi R Ivanova, Freddie Bickford Smith

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CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

Feb 27, 2023
Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster

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Do Bayesian Neural Networks Need To Be Fully Stochastic?

Nov 11, 2022
Mrinank Sharma, Sebastian Farquhar, Eric Nalisnick, Tom Rainforth

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Learning Instance-Specific Data Augmentations

May 31, 2022
Ning Miao, Emile Mathieu, Yann Dubois, Tom Rainforth, Yee Whye Teh, Adam Foster, Hyunjik Kim

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A Continuous Time Framework for Discrete Denoising Models

May 30, 2022
Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet

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Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation

Feb 14, 2022
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth

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Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods

Nov 03, 2021
Desi R. Ivanova, Adam Foster, Steven Kleinegesse, Michael U. Gutmann, Tom Rainforth

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Online Variational Filtering and Parameter Learning

Oct 26, 2021
Andrew Campbell, Yuyang Shi, Tom Rainforth, Arnaud Doucet

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Learning Multimodal VAEs through Mutual Supervision

Jul 01, 2021
Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, N. Siddharth

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