Michael Pearce
Michael Pearce
PhD Student, Warwick University
Verified email at warwick.ac.uk - Homepage
Title
Cited by
Cited by
Year
Scalable global optimization via local bayesian optimization
D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek
arXiv preprint arXiv:1910.01739, 2019
372019
Approaches to sample size calculation for clinical trials in rare diseases
F Miller, S Zohar, N Stallard, J Madan, M Posch, SW Hee, M Pearce, ...
Pharmaceutical statistics 17 (3), 214-230, 2018
172018
Recent advances in methodology for clinical trials in small populations: the InSPiRe project
T Friede, M Posch, S Zohar, C Alberti, N Benda, E Comets, S Day, ...
Orphanet journal of rare diseases 13 (1), 1-9, 2018
162018
Continuous multi-task bayesian optimisation with correlation
M Pearce, J Branke
European Journal of Operational Research 270 (3), 1074-1085, 2018
152018
Bayesian simulation optimization with input uncertainty
M Pearce, J Branke
Winter Simulation Conference, 2268 - 2278, 2017
122017
Value of information methods to design a clinical trial in a small population to optimise a health economic utility function
M Pearce, SW Hee, J Madan, M Posch, S Day, F Miller, S Zohar, ...
BMC medical research methodology 18 (1), 1-9, 2018
72018
Efficient expected improvement estimation for continuous multiple ranking and selection
M Pearce, J Branke
2017 Winter Simulation Conference (WSC), 2161-2172, 2017
62017
The gaussian process prior vae for interpretable latent dynamics from pixels
M Pearce
Symposium on Advances in Approximate Bayesian Inference, 1-12, 2020
42020
Comparing interpretable inference models for videos of physical motion
M Pearce, S Chiappa, U Paquet
1st Symposium on Advances in Approximate Bayesian Inference, 2018
42018
On parallelizing multi-task bayesian optimization
M Groves, M Pearce, J Branke
2018 Winter Simulation Conference (WSC), 1993-2002, 2018
32018
Scalable gaussian process variational autoencoders
M Jazbec, V Fortuin, M Pearce, S Mandt, G Rätsch
arXiv preprint arXiv:2010.13472, 2020
22020
Sparse Gaussian Process Variational Autoencoders
M Ashman, J So, W Tebbutt, V Fortuin, M Pearce, RE Turner
arXiv preprint arXiv:2010.10177, 2020
22020
Bayesian optimization allowing for common random numbers
M Pearce, M Poloczek, J Branke
arXiv preprint arXiv:1910.09259, 2019
22019
Factorized Gaussian Process Variational Autoencoders
M Jazbec, M Pearce, V Fortuin
arXiv preprint arXiv:2011.07255, 2020
12020
Bayesian Optimisation vs. Input Uncertainty Reduction
J Ungredda, M Pearce, J Branke
arXiv preprint arXiv:2006.00643, 2020
12020
Efficient Information Collection on Portfolios
M Pearce, J Branke
Warwick Research Archive Portal, 2017
12017
ConBO: Conditional Bayesian Optimization
M Pearce, J Klaise, M Groves
arXiv preprint arXiv:2002.09996, 2020
2020
Bayesian simulation optimization with common random numbers
M Pearce, M Poloczek, J Branke
2019 Winter Simulation Conference (WSC), 3492-3503, 2019
2019
Acquisition functions for simultaneous Bayesian optimisation of multiple problems
M Pearce
2017 Winter Simulation Conference (WSC), 4618-4619, 2017
2017
A value of information approach to optimal design of confirmatory clinical trials
N Stallard, M Pearce, SW Hee, J Madan, M Posch, S Day, F Miller, ...
TRIALS 18, 2017
2017
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