The StarCraft Multi-Agent Challenge M Samvelyan, T Rashid, C Schroeder de Witt, G Farquhar, N Nardelli, ...
Proceedings of the International Conference on Autonomous Agents and Multi …, 2019
753 2019 A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks A Filos, S Farquhar, AN Gomez, TGJ Rudner, Z Kenton, L Smith, ...
Technical Report, 2019
113 * 2019 Multi TGJ Rudner, M Rußwurm, J Fil, R Pelich, B Bischke, V Kopackova, ...
Proceedings of the AAAI Conference on Artificial Intelligence, 2019
98 2019 Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ...
Technical Report, 2021
79 2021 Plex: Towards Reliability using Pretrained Large Model Extensions D Tran, J Liu, MW Dusenberry, D Phan, M Collier, J Ren, K Han, Z Wang, ...
arXiv preprint arXiv:2207.07411, 2022
58 2022 VIREL: A Variational Inference Framework for Reinforcement Learning M Fellows, A Mahajan, TGJ Rudner, S Whiteson
Advances in Neural Information Processing Systems (NeurIPS), 2019
44 2019 Tractable Function-Space Variational Inference in Bayesian Neural Networks TGJ Rudner, Z Chen, YW Teh, Y Gal
Advances in Neural Information Processing Systems (NeurIPS), 2022
33 * 2022 Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks N Band, TGJ Rudner, Q Feng, A Filos, Z Nado, MW Dusenberry, G Jerfel, ...
Advances in Neural Information Processing Systems (NeurIPS), 2021
26 2021 Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations C Lu, PJ Ball, TGJ Rudner, J Parker-Holder, MA Osborne, YW Teh
Transactions on Machine Learning Research (TMLR), 2023
20 2023 Continual Learning via Sequential Function-Space Variational Inference TGJ Rudner, FB Smith, Q Feng, YW Teh, Y Gal
Proceedings of the International Conference on Machine Learning (ICML), 2022
20 2022 On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations TGJ Rudner, C Lu, MA Osborne, Y Gal, YW Teh
Advances in Neural Information Processing Systems (NeurIPS), 2021
16 2021 Outcome-Driven Reinforcement Learning via Variational Inference TGJ Rudner, VH Pong, R McAllister, Y Gal, S Levine
Advances in Neural Information Processing Systems (NeurIPS), 2021
13 2021 Inter-domain Deep Gaussian Processes TGJ Rudner, D Sejdinovic, Y Gal
Proceedings of the International Conference on Machine Learning (ICML), 2020
13 * 2020 On the Connection between Neural Processes and Gaussian Processes with Deep Kernels TGJ Rudner, V Fortuin, YW Teh, Y Gal
NeurIPS Workshop on Bayesian Deep Learning, 2018
13 2018 Key Concepts in AI Safety: Robustness and Adversarial Examples TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
10 2021 Key Concepts in AI Safety: An Overview TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
10 2021 Key Concepts in AI Safety: Specification in Machine Learning TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
7 2021 Protein Design with Guided Discrete Diffusion N Gruver, S Stanton, NC Frey, TGJ Rudner, I Hotzel, J Lafrance-Vanasse, ...
Advances in Neural Information Processing Systems (NeurIPS), 2023
5 2023 An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization R Shwartz-Ziv, R Balestriero, K Kawaguchi, TGJ Rudner, Y LeCun
Advances in Neural Information Processing Systems (NeurIPS), 2023
5 2023 Key Concepts in AI Safety: Interpretability in Machine Learning TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
5 2021 
Yarin GalAssociate Professor, University of OxfordПотвърден имейл адрес: cs.ox.ac.uk
