Chris. J. Oates
Chris. J. Oates
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Zitiert von
Zitiert von
Control functionals for Monte Carlo integration
CJ Oates, M Girolami, N Chopin
arXiv preprint arXiv:1410.2392, 2014
Probabilistic integration: A role in statistical computation?
FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic
Statistical Science 34 (1), 1-22, 2019
Bayesian probabilistic numerical methods
J Cockayne, CJ Oates, TJ Sullivan, M Girolami
SIAM Review 61 (4), 756-789, 2019
Network Inference and Biological Dynamics
CJ Oates, S Mukherjee
Arxiv preprint arXiv:1112.1047, 2011
Frank-Wolfe Bayesian quadrature: Probabilistic integration with theoretical guarantees
FX Briol, CJ Oates, M Girolami, MA Osborne
arXiv preprint arXiv:1506.02681, 2015
Stein points
WY Chen, L Mackey, J Gorham, FX Briol, C Oates
International Conference on Machine Learning, 844-853, 2018
Causal network inference using biochemical kinetics
CJ Oates, F Dondelinger, N Bayani, J Korkola, JW Gray, S Mukherjee
Bioinformatics 30 (17), i468-i474, 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
Convergence rates for a class of estimators based on Stein’s identity
CJ Oates, J Cockayne, FX Briol, M Girolami
arXiv preprint arXiv:1603.03220 6, 2016
Exact estimation of multiple directed acyclic graphs
CJ Oates, JQ Smith, S Mukherjee, J Cussens
Statistics and Computing 26 (4), 797-811, 2016
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), 1-14, 2016
A Bayes-Sard cubature method
T Karvonen, CJ Oates, S Särkkä
arXiv preprint arXiv:1804.03016, 2018
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
Probabilistic meshless methods for partial differential equations and Bayesian inverse problems
J Cockayne, C Oates, TJ Sullivan, M Girolami
A modern retrospective on probabilistic numerics
CJ Oates, TJ Sullivan
Statistics and Computing 29 (6), 1335-1351, 2019
Control functionals for quasi-Monte Carlo integration
C Oates, M Girolami
Artificial Intelligence and Statistics, 56-65, 2016
Bayesian probabilistic numerical methods in time-dependent state estimation for industrial hydrocyclone equipment
CJ Oates, J Cockayne, RG Aykroyd, M Girolami
Journal of the American Statistical Association 114 (528), 1518-1531, 2019
Investigation of the widely applicable Bayesian information criterion
N Friel, JP McKeone, CJ Oates, AN Pettitt
Statistics and Computing 27 (3), 833-844, 2017
A Bayesian conjugate gradient method (with discussion)
J Cockayne, CJ Oates, ICF Ipsen, M Girolami
Bayesian Analysis 14 (3), 937-1012, 2019
A stochastic model dissects cell states in biological transition processes
JW Armond, K Saha, AA Rana, CJ Oates, R Jaenisch, M Nicodemi, ...
Scientific reports 4 (1), 1-9, 2014
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