Non-linear Multitask Learning with Deep Gaussian Processes

no code implementations • 29 May 2019 • Ayman Boustati, Theodoros Damoulas, Richard S. Savage

We present a multi-task learning formulation for Deep Gaussian processes (DGPs), through non-linear mixtures of latent processes.

Benchmarking Gaussian Processes +1

Identifying cancer subtypes in glioblastoma by combining genomic, transcriptomic and epigenomic data

no code implementations • 12 Apr 2013 • Richard S. Savage, Zoubin Ghahramani, Jim E. Griffin, Paul Kirk, David L. Wild

We apply the method to 277 glioblastoma samples from The Cancer Genome Atlas, for which there are gene expression, copy number variation, methylation and microRNA data.

Clustering feature selection