257 citations · 405 across the 9 of their papers we have counts for
9 papers
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization
Valentin Breaz, Richard Wilkinson
Posterior sampling for high-dimensional Bayesian inverse problems is a common challenge in real-world applications. Randomized Maximum Likelihood (RML) is an optimization based met…
Adjoint-aided inference of Gaussian process driven differential equations
Paterne Gahungu, Christopher W Lanyon, Mauricio A Alvarez +3
Linear systems occur throughout engineering and the sciences, most notably as differential equations. In many cases the forcing function for the system is unknown, and interest lie…
Considering discrepancy when calibrating a mechanistic electrophysiology model
Chon Lok Lei, Sanmitra Ghosh, Dominic G. Whittaker +14
Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ me…
Quantifying Age and Model Uncertainties in Paleoclimate Data and Dynamical Climate Models with a Joint Inferential Analysis
Jake Carson, Michel Crucifix, Simon P. Preston +1
A major goal in paleoclimate science is to reconstruct historical climates using proxies for climate variables such as those observed in sediment cores, and in the process learn ab…
Detecting non-binomial sex allocation when developmental mortality operates
Richard D. Wilkinson, Apostolos Kapranas, Ian C. W. Hardy
Optimal sex allocation theory is one of the most intricately developed areas of evolutionary ecology. Under a range of conditions, particularly under population sub-division, selec…
ABC for climate: dealing with expensive simulators
Philip B. Holden, Neil R. Edwards, James Hensman +1
This paper is due to appear as a chapter of the forthcoming Handbook of Approximate Bayesian Computation (ABC) by S. Sisson, L. Fan, and M. Beaumont. We describe the challenge of c…
Bayesian model selection for the glacial-interglacial cycle
Jake Carson, Michel Crucifix, Simon Preston +1
A prevailing viewpoint in palaeoclimate science is that a single palaeoclimate record contains insufficient information to discriminate between most competing explanatory models. R…
Accelerating ABC methods using Gaussian processes
Richard D Wilkinson
Approximate Bayesian computation (ABC) methods are used to approximate posterior distributions using simulation rather than likelihood calculations. We introduce Gaussian process (…
Approximate Bayesian computation (ABC) gives exact results under the assumption of model error
Richard D. Wilkinson
Approximate Bayesian computation (ABC) or likelihood-free inference algorithms are used to find approximations to posterior distributions without making explicit use of the likelih…