| Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ... The Lancet Digital Health 2 (10), e537-e548, 2020 | 968 | 2020 |
| Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ... The Lancet Digital Health 2 (10), e549-e560, 2020 | 779 | 2020 |
| Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness S Vollmer, BA Mateen, G Bohner, FJ Király, R Ghani, P Jonsson, ... bmj 368, 2020 | 427 | 2020 |
| The bouncy particle sampler: A nonreversible rejection-free Markov chain Monte Carlo method A Bouchard-Côté, SJ Vollmer, A Doucet Journal of the American Statistical Association 113 (522), 855-867, 2018 | 312 | 2018 |
| Consistency and fluctuations for stochastic gradient Langevin dynamics YW Teh, AH Thiery, SJ Vollmer The Journal of Machine Learning Research 17 (1), 193-225, 2016 | 278 | 2016 |
| Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions M Hairer, AM Stuart, SJ Vollmer | 226 | 2014 |
| Improving survival of critical care patients with coronavirus disease 2019 in England: a national cohort study, March to June 2020 JM Dennis, AP McGovern, SJ Vollmer, BA Mateen Critical care medicine 49 (2), 209-214, 2021 | 213 | 2021 |
| Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol V Sounderajah, H Ashrafian, RM Golub, S Shetty, J De Fauw, L Hooft, ... BMJ open 11 (6), e047709, 2021 | 201 | 2021 |
| Type 2 diabetes and COVID-19–related mortality in the critical care setting: a national cohort study in England, March–July 2020 JM Dennis, BA Mateen, R Sonabend, NJ Thomas, KA Patel, AT Hattersley, ... Diabetes care 44 (1), 50-57, 2021 | 201 | 2021 |
| Exploration of the (non-) asymptotic bias and variance of stochastic gradient Langevin dynamics SJ Vollmer, KC Zygalakis, YW Teh Journal of Machine Learning Research 17 (159), 1-48, 2016 | 134 | 2016 |
| Measuring sample quality with diffusions J Gorham, AB Duncan, SJ Vollmer, L Mackey The Annals of Applied Probability 29 (5), 2884-2928, 2019 | 124 | 2019 |
| Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed Nature Medicine 25 (10), 1467-1468, 2019 | 95 | 2019 |
| Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server L Hasenclever, S Webb, T Lienart, S Vollmer, B Lakshminarayanan, ... Journal of Machine Learning Research 18 (106), 1-37, 2017 | 84* | 2017 |
| MLJ: A Julia package for composable machine learning AD Blaom, F Kiraly, T Lienart, Y Simillides, D Arenas, SJ Vollmer arXiv preprint arXiv:2007.12285, 2020 | 76 | 2020 |
| Digital health management during and beyond the COVID-19 pandemic: opportunities, barriers, and recommendations B Inkster, R O’Brien, E Selby, S Joshi, V Subramanian, M Kadaba, ... JMIR mental health 7 (7), e19246, 2020 | 75 | 2020 |
| Improving the quality of machine learning in health applications and clinical research BA Mateen, J Liley, AK Denniston, CC Holmes, SJ Vollmer Nature Machine Intelligence 2 (10), 554-556, 2020 | 73 | 2020 |
| Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains J Bierkens, A Bouchard-Côté, A Doucet, AB Duncan, P Fearnhead, ... Statistics & Probability Letters 136, 148-154, 2018 | 67 | 2018 |
| The true cost of stochastic gradient Langevin dynamics T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ... arXiv preprint arXiv:1706.02692, 2017 | 66 | 2017 |
| COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records JH Thygesen, C Tomlinson, S Hollings, MA Mizani, A Handy, A Akbari, ... The Lancet Digital Health 4 (7), e542-e557, 2022 | 64 | 2022 |
| Posterior consistency for Bayesian inverse problems through stability and regression results SJ Vollmer Inverse Problems 29 (12), 125011, 2013 | 62 | 2013 |