625 citations · 2.7k across the 69 of their papers we have counts for
5 papers · 2 filters
Spatio-temporal Gaussian processes modeling of dynamical systems in systems biology
Mu Niu, Zhenwen Dai, Neil Lawrence +1
Quantitative modeling of post-transcriptional regulation process is a challenging problem in systems biology. A mechanical model of the regulatory process needs to be able to descr…
Parallelizable sparse inverse formulation Gaussian processes (SpInGP)
Alexander Grigorievskiy, Neil Lawrence, Simo Särkkä
We propose a parallelizable sparse inverse formulation Gaussian process (SpInGP) for temporal models. It uses a sparse precision GP formulation and sparse matrix routines to speed…
Differentially Private Gaussian Processes
Michael Thomas Smith, Max Zwiessele, Neil D. Lawrence
A major challenge for machine learning is increasing the availability of data while respecting the privacy of individuals. Here we combine the provable privacy guarantees of the di…
Chained Gaussian Processes
Alan D. Saul, James Hensman, Aki Vehtari +1
Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner o…
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis
Andreas Damianou, Neil D. Lawrence, Carl Henrik Ek
Factor analysis aims to determine latent factors, or traits, which summarize a given data set. Inter-battery factor analysis extends this notion to multiple views of the data. In t…