1 citations · 1 across the 1 of their papers we have counts for
3 papers
stat.ML2019
Black-Box Inference for Non-Linear Latent Force Models
Wil O. C. Ward, Tom Ryder, Dennis Prangle +1
Latent force models are systems whereby there is a mechanistic model describing the dynamics of the system state, with some unknown forcing term that is approximated with a Gaussia…
cs.LG2019★ 1 cited
Variational bridge constructs for approximate Gaussian process regression
Wil O C Ward, Mauricio A Álvarez
This paper introduces a method to approximate Gaussian process regression by representing the problem as a stochastic differential equation and using variational inference to appro…
stat.ML2018
Non-linear process convolutions for multi-output Gaussian processes
Mauricio A. Álvarez, Wil O. C. Ward, Cristian Guarnizo
The paper introduces a non-linear version of the process convolution formalism for building covariance functions for multi-output Gaussian processes. The non-linearity is introduce…