308 citations · 980 across the 64 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…
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
Creighton Heaukulani, Mark van der Wilk
We implement gradient-based variational inference routines for Wishart and inverse Wishart processes, which we apply as Bayesian models for the dynamic, heteroskedastic covariance…
Rates of Convergence for Sparse Variational Gaussian Process Regression
David R. Burt, Carl E. Rasmussen, Mark van der Wilk
Excellent variational approximations to Gaussian process posteriors have been developed which avoid the scaling with dataset size . They reduce 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…