3 citations · 3 across the 3 of their papers we have counts for
3 papers
Gaussian Processes on Hypergraphs
Thomas Pinder, Kathryn Turnbull, Christopher Nemeth +1
We derive a Matern Gaussian process (GP) on the vertices of a hypergraph. This enables estimation of regression models of observed or latent values associated with the vertices, in…
A Probabilistic Assessment of the COVID-19 Lockdown on Air Quality in the UK
Thomas Pinder, Michael Hollaway, Christopher Nemeth +2
In March 2020 the United Kingdom (UK) entered a nationwide lockdown period due to the Covid-19 pandemic. As a result, levels of nitrogen dioxide (NO2) in the atmosphere dropped. In…
Stein Variational Gaussian Processes
Thomas Pinder, Christopher Nemeth, David Leslie
We show how to use Stein variational gradient descent (SVGD) to carry out inference in Gaussian process (GP) models with non-Gaussian likelihoods and large data volumes. Markov cha…