140 citations · 1.9k across the 86 of their papers we have counts for
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Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices
Jan Povala, Ieva Kazlauskaite, Eky Febrianto +2
Inverse problems involving partial differential equations (PDEs) are widely used in science and engineering. Although such problems are generally ill-posed, different regularisatio…
Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes
Jan Povala, Seppo Virtanen, Mark Girolami
To obtain operational insights regarding the crime of burglary in London we consider the estimation of effects of covariates on the intensity of spatial point patterns. By taking i…
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…
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…
Bayesian modelling and quantification of Raman spectroscopy
Matthew Moores, Kirsten Gracie, Jake Carson +3
Raman spectroscopy can be used to identify molecules such as DNA by the characteristic scattering of light from a laser. It is sensitive at very low concentrations and can accurate…
Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities
M. Filippone, A. F. Marquand, C. R. V. Blain +3
For many neurological disorders, prediction of disease state is an important clinical aim. Neuroimaging provides detailed information about brain structure and function from which…