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
469 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
84 * 2019 Multi TGJ Rudner, M Rußwurm, J Fil, R Pelich, B Bischke, V Kopackova, ...
Proceedings of the AAAI Conference on Artificial Intelligence, 2019
74 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
43 2021 VIREL: A Variational Inference Framework for Reinforcement Learning M Fellows, A Mahajan, TGJ Rudner, S Whiteson
Advances in Neural Information Processing Systems, 2019
37 2019 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
22 2022 Tractable Function-Space Variational Inference in Bayesian Neural Networks TGJ Rudner, Z Chen, YW Teh, Y Gal
Symposium on Advances in Approximate Bayesian Inference, 2021
18 * 2021 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, 2021
13 2021 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
12 2018 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, 2021
10 2021 Outcome-Driven Reinforcement Learning via Variational Inference TGJ Rudner, VH Pong, R McAllister, Y Gal, S Levine
Advances in Neural Information Processing Systems, 2021
8 2021 Inter-domain Deep Gaussian Processes TGJ Rudner, D Sejdinovic, Y Gal
Proceedings of the International Conference on Machine Learning, 2020
8 * 2020 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, 2022
6 2022 Key Concepts in AI Safety: An Overview TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
6 2021 Challenges and opportunities in offline reinforcement learning from visual observations C Lu, PJ Ball, TGJ Rudner, J Parker-Holder, MA Osborne, YW Teh
arXiv preprint arXiv:2206.04779, 2022
4 2022 Key Concepts in AI Safety: Specification in Machine Learning TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
4 2021 The Natural Neural Tangent Kernel: Neural Network Training Dynamics under Natural Gradient Descent TGJ Rudner, F Wenzel, YW Teh, Y Gal
NeurIPS Workshop on Bayesian Deep Learning, 2019
4 2019 Key Concepts in AI Safety: Robustness and Adversarial Examples TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
3 2021 On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes TGJ Rudner, O Key, Y Gal, T Rainforth
Proceedings of the International Conference on Machine Learning, 2021
1 2021 Key Concepts in AI Safety: Interpretability in Machine Learning TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
1 2021 
Yarin GalAssociate Professor, University of OxfordZweryfikowany adres z cs.ox.ac.uk
