140 citations · 1.9k across the 86 of their papers we have counts for
8 papers · 1 filter
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success
Richard Scalzo, David Kohn, Hugo Olierook +4
The rigorous quantification of uncertainty in geophysical inversions is a challenging problem. Inversions are often ill-posed and the likelihood surface may be multi-modal; propert…
Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?"
Francois-Xavier Briol, Chris J. Oates, Mark Girolami +2
This article is the rejoinder for the paper "Probabilistic Integration: A Role in Statistical Computation?" to appear in Statistical Science with discussion. We would first like to…
The synthesis of data from instrumented structures and physics-based models via Gaussian processes
Alastair Gregory, Din-Houn Lau, Mark Girolami +2
A recent development which is poised to disrupt current structural engineering practice is the use of data obtained from physical structures such as bridges, viaducts and buildings…
A Riemann-Stein Kernel Method
Alessandro Barp, Chris. J. Oates, Emilio Porcu +1
This paper proposes and studies a numerical method for approximation of posterior expectations based on interpolation with a Stein reproducing kernel. Finite-sample-size bounds on…
Stochastic Modelling of Urban Structure
L. Ellam, M. Girolami, G. A. Pavliotis +1
The building of mathematical and computer models of cities has a long history. The core elements are models of flows (spatial interaction) and the dynamics of structural evolution.…
Posterior Inference for Sparse Hierarchical Non-stationary Models
Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade +2
Gaussian processes are valuable tools for non-parametric modelling, where typically an assumption of stationarity is employed. While removing this assumption can improve prediction…