Control functionals for Monte Carlo integration CJ Oates, M Girolami, N Chopin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 242 | 2017 |
Probabilistic integration FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic Statistical Science 34 (1), 1-22, 2019 | 209* | 2019 |
Bayesian probabilistic numerical methods J Cockayne, CJ Oates, TJ Sullivan, M Girolami SIAM review 61 (4), 756-789, 2019 | 182 | 2019 |
Stein points WY Chen, L Mackey, J Gorham, FX Briol, C Oates International Conference on Machine Learning, 844-853, 2018 | 101 | 2018 |
Network Inference and Biological Dynamics CJ Oates, S Mukherjee Arxiv preprint arXiv:1112.1047, 2011 | 98 | 2011 |
Frank-Wolfe Bayesian quadrature: Probabilistic integration with theoretical guarantees FX Briol, C Oates, M Girolami, MA Osborne Advances in Neural Information Processing Systems 28, 2015 | 88 | 2015 |
A modern retrospective on probabilistic numerics CJ Oates, TJ Sullivan Statistics and computing 29 (6), 1335-1351, 2019 | 81 | 2019 |
Stein’s method meets computational statistics: A review of some recent developments A Anastasiou, A Barp, FX Briol, B Ebner, RE Gaunt, F Ghaderinezhad, ... Statistical Science 38 (1), 120-139, 2023 | 66 | 2023 |
Probabilistic numerical methods for partial differential equations and Bayesian inverse problems J Cockayne, C Oates, T Sullivan, M Girolami arXiv preprint arXiv:1605.07811, 2016 | 66* | 2016 |
Stein point markov chain monte carlo WY Chen, A Barp, FX Briol, J Gorham, M Girolami, L Mackey, C Oates International Conference on Machine Learning, 1011-1021, 2019 | 64 | 2019 |
Robust generalised Bayesian inference for intractable likelihoods T Matsubara, J Knoblauch, FX Briol, CJ Oates Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 63 | 2022 |
Causal network inference using biochemical kinetics CJ Oates, F Dondelinger, N Bayani, J Korkola, JW Gray, S Mukherjee Bioinformatics 30 (17), i468-i474, 2014 | 63 | 2014 |
The controlled thermodynamic integral for Bayesian model evidence evaluation CJ Oates, T Papamarkou, M Girolami Journal of the American Statistical Association 111 (514), 634-645, 2016 | 56 | 2016 |
Optimal thinning of MCMC output M Riabiz, WY Chen, J Cockayne, P Swietach, SA Niederer, L Mackey, ... Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 54 | 2022 |
Convergence rates for a class of estimators based on Stein’s method CJ Oates, J Cockayne, FX Briol, M Girolami | 53 | 2019 |
A Bayes-Sard cubature method T Karvonen, CJ Oates, S Sarkka Advances in Neural Information Processing Systems 31, 2018 | 51* | 2018 |
RNA editing generates cellular subsets with diverse sequence within populations D Harjanto, T Papamarkou, CJ Oates, V Rayon-Estrada, FN Papavasiliou, ... Nature communications 7 (1), 12145, 2016 | 49 | 2016 |
A Riemann–Stein kernel method A Barp, CJ Oates, E Porcu, M Girolami Bernoulli 28 (4), 2181-2208, 2022 | 48* | 2022 |
Exact estimation of multiple directed acyclic graphs CJ Oates, JQ Smith, S Mukherjee, J Cussens Statistics and Computing 26, 797-811, 2016 | 46 | 2016 |
A Bayesian conjugate gradient method (with discussion) J Cockayne, CJ Oates, ICF Ipsen, M Girolami | 44* | 2019 |