417 citations · 1.7k across the 36 of their papers we have counts for
3 papers · 1 filter
Gaussian Processes for Big Data
James Hensman, Nicolo Fusi, Neil D. Lawrence
We introduce stochastic variational inference for Gaussian process models. This enables the application of Gaussian process (GP) models to data sets containing millions of data poi…
Fast Approximate Inference of Transcript Expression Levels from RNA-seq Data
James Hensman, Peter Glaus, Antti Honkela +1
Motivation: The mapping of RNA-seq reads to their transcripts of origin is a fundamental task in transcript expression estimation and differential expression scoring. Where ambigui…
Gaussian process models for periodicity detection
Nicolas Durrande, James Hensman, Magnus Rattray +1
We consider the problem of detecting and quantifying the periodic component of a function given noise-corrupted observations of a limited number of input/output tuples. Our approac…