| A useful variant of the Davis–Kahan theorem for statisticians Y Yu, T Wang, RJ Samworth Biometrika 102 (2), 315-323, 2015 | 675 | 2015 |
| High dimensional change point estimation via sparse projection T Wang, RJ Samworth Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2018 | 243 | 2018 |
| Multiple identifications in multi-armed bandits S Bubeck, T Wang, N Viswanathan International Conference on Machine Learning, 258-265, 2013 | 233 | 2013 |
| Statistical and computational trade-offs in estimation of sparse principal components T Wang, Q Berthet, RJ Samworth | 165 | 2016 |
| Isotonic regression in general dimensions Q Han, T Wang, S Chatterjee, RJ Samworth | 117 | 2019 |
| INSIGHT: A population-scale COVID-19 testing strategy combining point-of-care diagnosis with centralized high-throughput sequencing Q Wu, C Suo, T Brown, T Wang, SA Teichmann, AR Bassett bioRxiv, 2020.06. 01.127019, 2020 | 72* | 2020 |
| High-dimensional principal component analysis with heterogeneous missingness Z Zhu, T Wang, RJ Samworth Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 55 | 2022 |
| High-dimensional, multiscale online changepoint detection Y Chen, T Wang, RJ Samworth Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 47 | 2022 |
| Average-case hardness of RIP certification T Wang, Q Berthet, Y Plan Advances in Neural Information Processing Systems 29, 2016 | 47 | 2016 |
| Machine-learning approach for predicting the discharging capacities of doped lithium nickel–cobalt–manganese cathode materials in Li-ion batteries G Wang, T Fearn, T Wang, KL Choy ACS central science 7 (9), 1551-1560, 2021 | 32 | 2021 |
| Sparse principal component analysis via axis-aligned random projections M Gataric, T Wang, RJ Samworth Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020 | 25* | 2020 |
| Development of a prognostic model that predicts survival after pancreaticoduodenectomy for ampullary cancer M Feretis, T Wang, S Iype, A Duckworth, R Brais, B Basu, NV Jamieson, ... Pancreas 46 (10), 1314-1321, 2017 | 15 | 2017 |
| Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons Q Wu, J Wu, K Karim, X Chen, T Wang, S Iwama, S Carobbio, P Keen, ... Molecular Cell 83 (7), 1125-1139. e8, 2023 | 11 | 2023 |
| High-dimensional changepoint estimation with heterogeneous missingness B Follain, T Wang, RJ Samworth Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 11 | 2022 |
| Monitoring network changes in social media CYH Chen, Y Okhrin, T Wang Journal of Business & Economic Statistics, 1-16, 2022 | 11 | 2022 |
| Insight Gained from Using Machine Learning Techniques to Predict the Discharge Capacities of Doped Spinel Cathode Materials for Lithium‐Ion Batteries Applications G Wang, T Fearn, T Wang, KL Choy Energy Technology 9 (5), 2100053, 2021 | 9 | 2021 |
| The impact of severe acute kidney injury requiring renal replacement therapy on survival and renal function of heart transplant recipients–a UK cohort study L Wang, T Wang, SN Rushton, G Parry, JH Dark, NS Sheerin Transplant International 33 (12), 1650-1666, 2020 | 9 | 2020 |
| Multicentre study of physical abuse and limb fractures in young children in the East Anglia Region, UK PD Mitchell, R Brown, T Wang, RD Shah, RJ Samworth, S Deakin, P Edge, ... Archives of disease in childhood 104 (10), 956-961, 2019 | 9 | 2019 |
| Comprehensive classification of anatomical variants of the main biliary ducts BV Janssen, S van Laarhoven, M Elshaer, H Cai, R Praseedom, T Wang, ... British Journal of Surgery 108 (5), 458-462, 2021 | 8 | 2021 |
| Automatic change-point detection in time series via deep learning J Li, P Fearnhead, P Fryzlewicz, T Wang Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2024 | 6 | 2024 |
Yi YuDepartment of Statistics, University of WarwickVerified email at warwick.ac.uk
