| Age groups that sustain resurging COVID-19 epidemics in the United States M Monod, A Blenkinsop, X Xi, D Hebert, S Bershan, S Tietze, M Baguelin, ... Science 371 (6536), eabe8372, 2021 | 240 | 2021 |
| State-level tracking of COVID-19 in the United States HJT Unwin, S Mishra, VC Bradley, A Gandy, TA Mellan, H Coupland, ... Nature communications 11 (1), 6189, 2020 | 151 | 2020 |
| Report 21: Estimating COVID-19 cases and reproduction number in Brazil TA Mellan, HH Hoeltgebaum, S Mishra, C Whittaker, RP Schnekenberg, ... medRxiv, 2020 | 130 | 2020 |
| Report 20: Using mobility to estimate the transmission intensity of COVID-19 in Italy: a subnational analysis with future scenarios MAC Vollmer, S Mishra, HJT Unwin, A Gandy, TA Mellan, H Zhu, ... Imperial College COVID-19 Response Team May, 2020 | 63* | 2020 |
| Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, and Hyunjik Kim. Lietransformer: Equivariant self-attention for lie groups MJ Hutchinson International Conference on Machine Learning, 4533-4543, 2020 | 36* | 2020 |
| Riemannian score-based generative modeling V De Bortoli, E Mathieu, M Hutchinson, J Thornton, YW Teh, A Doucet arXiv preprint arXiv:2202.02763, 2022 | 29 | 2022 |
| LieTransformer: Equivariant self-attention for Lie Groups M Hutchinson, C Le Lan, S Zaidi, E Dupont, YW Teh, H Kim arXiv preprint arXiv:2012.10885, 2020 | 29 | 2020 |
| Subnational analysis of the COVID-19 epidemic in Brazil TA Mellan, HH Hoeltgebaum, S Mishra, C Whittaker, RP Schnekenberg, ... MedRxiv, 2020 | 18 | 2020 |
| Equivariant learning of stochastic fields: Gaussian processes and steerable conditional neural processes P Holderrieth, MJ Hutchinson, YW Teh International Conference on Machine Learning, 4297-4307, 2021 | 17 | 2021 |
| Vector-valued Gaussian processes on Riemannian manifolds via gauge independent projected kernels M Hutchinson, A Terenin, V Borovitskiy, S Takao, Y Teh, M Deisenroth Advances in Neural Information Processing Systems 34, 17160-17169, 2021 | 10 | 2021 |
| Effectiveness and resource requirements of test, trace and isolate strategies for COVID in the UK B He, S Zaidi, B Elesedy, M Hutchinson, A Paleyes, G Harling, ... Royal Society open science 8 (3), 201491, 2021 | 8* | 2021 |
| Report 20: Using mobility to estimate the transmission intensity of COVID-19 in Italy: A subnational analysis with future scenarios. medRxiv [Preprint](2020) MAC Vollmer, S Mishra, HJT Unwin, A Gandy, TA Mellan, V Bradley, ... Google Scholar, 2021 | 7 | 2021 |
| Imperial College COVID-19 Response Team M Monod, A Blenkinsop, X Xi, D Hebert, S Bershan, S Tietze, M Baguelin, ... Age groups that sustain resurging COVID-19 epidemics in the United States …, 2021 | 7 | 2021 |
| Efficient Bayesian inference of instantaneous reproduction numbers at fine spatial scales, with an application to mapping and nowcasting the Covid-19 epidemic in British local … YW Teh, B Elesedy, B He, M Hutchinson, S Zaidi, A Bhoopchand, ... Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022 | 5 | 2022 |
| Differentially private federated variational inference M Sharma, M Hutchinson, S Swaroop, A Honkela, RE Turner arXiv preprint arXiv:1911.10563, 2019 | 5 | 2019 |
| Report 21: Estimating COVID-19 Cases and Reproduction Number in Brazil (2020) TA Mellan, HH Hoeltgebaum, S Mishra, C Whittaker, RP Schnekenberg, ... URL https://doi. org/10.25561/78872, 0 | 5 | |
| Spectral Diffusion Processes A Phillips, T Seror, M Hutchinson, V De Bortoli, A Doucet, E Mathieu arXiv preprint arXiv:2209.14125, 2022 | 3 | 2022 |
| Authors’ Reply to the Discussion of ‘Efficient Bayesian Inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting … YW Teh, B Elesedy, B He, M Hutchinson, S Zaidi, A Bhoopchand, ... Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022 | | 2022 |
| Score-based Generative Models on Euclidean space and Riemannian manifolds M Hutchinson, É Mathieu | | 2022 |
| Riemannian Diffusion Schr\" odinger Bridge J Thornton, M Hutchinson, E Mathieu, V De Bortoli, YW Teh, A Doucet arXiv preprint arXiv:2207.03024, 2022 | | 2022 |
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
