Tim G. J. Rudner - Google Scholar

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Citations	98	98
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i10-index	4	4

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2019202035 62

Co-authors

Shimon WhitesonProfessor of Computer Science, University of OxfordVerified email at cs.ox.ac.uk
Yarin GalAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Vincent FortuinPhD student, ETH ZürichVerified email at inf.ethz.ch
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk

Tim G. J. Rudner

Tim G. J. Rudner

PhD Candidate in Computer Science, University of Oxford

Verified email at cs.ox.ac.uk - Homepage

Machine Learning Bayesian Deep Learning Variational Inference Reinforcement Learning


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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	49	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 33, 2019	23	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, ... arXiv preprint arXiv:1912.10481, 2019	14*	2019
VIREL: A Variational Inference Framework for Reinforcement Learning M Fellows, A Mahajan, TGJ Rudner, S Whiteson Advances in Neural Information Processing Systems, 7122-7136, 2019	10	2019
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	2	2018

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Articles 1–5