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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning


Jun 07, 2021
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran


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Outcome-Driven Reinforcement Learning via Variational Inference


Apr 20, 2021
Tim G. J. Rudner, Vitchyr H. Pong, Rowan McAllister, Yarin Gal, Sergey Levine


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On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes


Nov 01, 2020
Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth


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Inter-domain Deep Gaussian Processes


Nov 01, 2020
Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal

* Published in Proceedings of the 37th International Conference on Machine Learning (ICML 2020) 

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A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks


Dec 22, 2019
Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal


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The StarCraft Multi-Agent Challenge


Feb 26, 2019
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob Foerster, Shimon Whiteson


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Multi$^{\mathbf{3}}$Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery


Dec 05, 2018
Tim G. J. Rudner, Marc Rußwurm, Jakub Fil, Ramona Pelich, Benjamin Bischke, Veronika Kopackova, Piotr Bilinski

* To appear in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) 

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VIREL: A Variational Inference Framework for Reinforcement Learning


Nov 03, 2018
Matthew Fellows, Anuj Mahajan, Tim G. J. Rudner, Shimon Whiteson


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