6 papers
Beyond Laplace: Closed-form wrapped Gaussian posterior approximations on statistical manifolds
Marcelo Hartmann, Luu Hoang Phuc Hau, Anton Mallasto +8
In Bayesian statistics, the Laplace approximation provides a computationally efficient approximation to posterior distributions. However, its Gaussian form restricts it to elliptic…
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…
Error analysis for a statistical finite element method
Toni Karvonen, Fehmi Cirak, Mark Girolami
The recently proposed statistical finite element (statFEM) approach synthesises measurement data with finite element models and allows for making predictions about the unknown true…
Targeted Separation and Convergence with Kernel Discrepancies
Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami +1
Maximum mean discrepancies (MMDs) like the kernel Stein discrepancy (KSD) have grown central to a wide range of applications, including hypothesis testing, sampler selection, distr…
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Ã. Deniz Akyildiz, Francesca Romana Crucinio, Mark Girolami +2
We develop a class of interacting particle systems for implementing a maximum marginal likelihood estimation (MMLE) procedure to estimate the parameters of a latent variable model.…
Meta-models for transfer learning in source localisation
Lawrence A. Bull, Matthew R. Jones, Elizabeth J. Cross +2
In practice, non-destructive testing (NDT) procedures tend to consider experiments (and their respective models) as distinct, conducted in isolation and associated with independent…