Tim G. J. Rudner
Tim G. J. Rudner
PhD Candidate in Computer Science, University of Oxford
Vahvistettu sähköpostiosoite verkkotunnuksessa cs.ox.ac.uk - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
The StarCraft Multi-Agent Challenge
M Samvelyan, T Rashid, C Schroeder de Witt, G Farquhar, N Nardelli, ...
Proceedings of the 18th International Conference on Autonomous Agents and …, 2019
1062019
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 33, 2019
402019
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
A Filos, S Farquhar, AN Gomez, TGJ Rudner, Z Kenton, L Smith, ...
arXiv preprint arXiv:1912.10481, 2019
26*2019
VIREL: A Variational Inference Framework for Reinforcement Learning
M Fellows, A Mahajan, TGJ Rudner, S Whiteson
Advances in Neural Information Processing Systems, 2019
192019
On the Connection between Neural Processes and Gaussian Processes with Deep Kernels
TGJ Rudner, V Fortuin, YW Teh, Y Gal
Workshop on Bayesian Deep Learning (NeurIPS 2018), Montréal, Canada, 2018
52018
Inter-domain Deep Gaussian Processes
TGJ Rudner, D Sejdinovic, Y Gal
Proceedings of the 37th International Conference on Machine Learning, 2020
3*2020
The Natural Neural Tangent Kernel: Neural Network Training Dynamics under Natural Gradient Descent
TGJ Rudner, F Wenzel, YW Teh, Y Gal
Workshop on Bayesian Deep Learning (NeurIPS 2019), Vancouver, Canada, 2019
22019
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes
TGJ Rudner, O Key, Y Gal, T Rainforth
arXiv preprint arXiv:2011.00515, 2020
2020
Outcome-Driven Reinforcement Learning via Variational Inference
TGJ Rudner, VH Pong, R McAllister, Y Gal, S Levine
2020
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Artikkelit 1–9