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Tim G. J. Rudner
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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
11442019
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
147*2019
MultiNet: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
TGJ Rudner, M Rußwurm, J Fil, R Pelich, B Bischke, V Kopackova, ...
Proceedings of the AAAI Conference on Artificial Intelligence, 2019
1362019
Plex: Towards Reliability using Pretrained Large Model Extensions
D Tran, J Liu, MW Dusenberry, D Phan, M Collier, J Ren, K Han, Z Wang, ...
ICML Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward, 2022
1252022
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ...
Technical Report, 2021
1112021
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
992023
VIREL: A Variational Inference Framework for Reinforcement Learning
M Fellows, A Mahajan, TGJ Rudner, S Whiteson
Advances in Neural Information Processing Systems (NeurIPS), 2019
622019
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
61*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
542021
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
442023
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
402022
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ...
Proceedings of the International Conference on Machine Learning (ICML), 2024
32*2024
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
28*2023
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
272021
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
YL Li, TGJ Rudner, AG Wilson
International Conference on Learning Representations (ICLR), 2024
182024
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
172021
Key Concepts in AI Safety: An Overview
TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
172021
Key Concepts in AI Safety: Robustness and Adversarial Examples
TGJ Rudner, H Toner
Georgetown University Center for Security & Emerging Technology Issue Briefs, 2021
152021
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
152018
Non-vacuous Generalization Bounds for Large Language Models
S Lotfi, M Finzi, Y Kuang, TGJ Rudner, M Goldblum, AG Wilson
Proceedings of the International Conference on Machine Learning (ICML), 2024
142024
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Articles 1–20