Accelerating ABC methods using Gaussian processes. - Richard Wilkinson (AISTATS, 2014)

Gaussian process emulators for quantifying uncertainty in CO2 spreading predictions in heterogeneous media. - Liang Tian; Richard Wilkinson; Zhibing Yang; Henry Power; Fritjof Fagerlund; Auli Niemi (Comput. Geosci., 2017)

An Algorithm to Sample an Anatomy With Uncertainty. - Cesare Corrado; Steven Williams 001; Iain Sim; Sam Coveney; Mark D. O'Neill; Richard Wilkinson; Jeremy E. Oakley; Richard H. Clayton; Steven A. Niederer (CinC, 2018)

Anomaly Detection Semi-Supervised Framework for Sepsis Treatment. - Ines Krissaane; Kingsley Hampton; Jumanah Alshenaifi; Richard Wilkinson (CinC, 2019)

Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity. - Sam Coveney; Cesare Corrado; Caroline H. Roney; Daniel O'Hare; Steven E. Williams; Mark D. O'Neill; Steven A. Niederer; Richard H. Clayton; Jeremy E. Oakley; Richard D. Wilkinson (CoRR, 2020)

Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions. - Cesare Corrado; Orod Razeghi; Caroline H. Roney; Sam Coveney; Steven Williams 001; Iain Sim; Mark D. O'Neill; Richard Wilkinson; Jeremy E. Oakley; Richard H. Clayton; Steven A. Niederer (Medical Image Anal., 2020)

Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds. - Sam Coveney; Richard H. Clayton; Cesare Corrado; Caroline H. Roney; Richard Wilkinson; Jeremy E. Oakley; Finn Lindgren; Steven E. Williams; Mark D. O'Neill; Steven A. Niederer (IEEE Trans. Biomed. Eng., 2020)

A Workflow for Probabilistic Calibration of Models of Left Atrial Electrophysiology. - Sam Coveney; Cesare Corrado; Caroline H. Roney; Richard D. Wilkinson; Jeremy E. Oakley; Steven A. Niederer; Richard H. Clayton (CinC, 2022)

Adjoint-aided inference of Gaussian process driven differential equations. - Paterne Gahungu; Christopher W. Lanyon; Mauricio A. Álvarez; Engineer Bainomugisha; Michael T. Smith 003; Richard Wilkinson (NeurIPS, 2022)

Modelling calibration uncertainty in networks of environmental sensors. - Michael Thomas Smith; Magnus Ross; Joel Ssematimba; Pablo A. Alvarado; Mauricio A. Álvarez; Engineer Bainomugisha; Richard Wilkinson (CoRR, 2022)

Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators. - Marina Strocchi; Stefano Longobardi; Christoph M. Augustin; Matthias A. F. Gsell; Argyrios Petras; Christopher A. Rinaldi; Edward J. Vigmond; Gernot Plank; Chris J. Oates; Richard D. Wilkinson; Steven A. Niederer (PLoS Comput. Biol., 2023)

Quantifying the impact of shape uncertainty on predicted arrhythmias. - Cesare Corrado; Caroline H. Roney; Orod Razeghi; José Alonso Solís-Lemus; Sam Coveney; Iain Sim; Steven E. Williams; Mark D. O'Neill; Richard D. Wilkinson; Richard H. Clayton; Steven A. Niederer (Comput. Biol. Medicine, 2023)

Randomized Maximum Likelihood Via High-Dimensional Bayesian Optimization. - Valentin Breaz; Richard Wilkinson (ICASSP, 2024)