742 citations
- Wellcome TrustGB18 papers
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5 papers · 1 filter
Kernel Identification Through Transformers
Fergus Simpson, Ian Davies, Vidhi Lalchand +3
Kernel selection plays a central role in determining the performance of Gaussian Process (GP) models, as the chosen kernel determines both the inductive biases and prior support of…
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties
Jakob Lindinger, David Reeb, Christoph Lippert +1
Deep Gaussian Processes learn probabilistic data representations for supervised learning by cascading multiple Gaussian Processes. While this model family promises flexible predict…
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
David Reeb, Andreas Doerr, Sebastian Gerwinn +1
Gaussian Processes (GPs) are a generic modelling tool for supervised learning. While they have been successfully applied on large datasets, their use in safety-critical application…
Modelling-based experiment retrieval: A case study with gene expression clustering
Paul Blomstedt, Ritabrata Dutta, Sohan Seth +2
Motivation: Public and private repositories of experimental data are growing to sizes that require dedicated methods for finding relevant data. To improve on the state of the art o…
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
Song Liu, Makoto Yamada, Nigel Collier +1
The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection a…