65 citations · 247 across the 12 of their papers we have counts for
4 papers · 1 filter
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
Alessandro Davide Ialongo, Mark van der Wilk, James Hensman +1
We identify a new variational inference scheme for dynamical systems whose transition function is modelled by a Gaussian process. Inference in this setting has either employed comp…
Deep Gaussian Processes with Importance-Weighted Variational Inference
Hugh Salimbeni, Vincent Dutordoir, James Hensman +1
Deep Gaussian processes (DGPs) can model complex marginal densities as well as complex mappings. Non-Gaussian marginals are essential for modelling real-world data, and can be gene…
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era
Nicolas Durrande, Vincent Adam, Lucas Bordeaux +2
Banded matrices can be used as precision matrices in several models including linear state-space models, some Gaussian processes, and Gaussian Markov random fields. The aim of the…
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Vincent Dutordoir, Mark van der Wilk, Artem Artemev +1
In decision-making systems, it is important to have classifiers that have calibrated uncertainties, with an optimisation objective that can be used for automated model selection an…