65 citations · 100 across the 12 of their papers we have counts for
3 papers · 1 filter
A Framework for Interdomain and Multioutput Gaussian Processes
Mark van der Wilk, Vincent Dutordoir, ST John +3
One obstacle to the use of Gaussian processes (GPs) in large-scale problems, and as a component in deep learning system, is the need for bespoke derivations and implementations for…
Non-linear regression models for behavioral and neural data analysis
Vincent Adam, Alexandre Hyafil
Regression models are popular tools in empirical sciences to infer the influence of a set of variables onto a dependent variable given an experimental dataset. In neuroscience and…
Doubly Sparse Variational Gaussian Processes
Vincent Adam, Stefanos Eleftheriadis, Nicolas Durrande +2
The use of Gaussian process models is typically limited to datasets with a few tens of thousands of observations due to their complexity and memory footprint. The two most commonly…