Search Results for author: Oliver Hamelijnck

Found 4 papers, 3 papers with code

Non-separable Non-stationary random fields

no code implementations ICML 2020 Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark Steel

We describe a framework for constructing non-separable non-stationary random fields that is based on an infinite mixture of convolved stochastic processes.

Spatio-Temporal Variational Gaussian Processes

1 code implementation NeurIPS 2021 Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas

We introduce a scalable approach to Gaussian process inference that combines spatio-temporal filtering with natural gradient variational inference, resulting in a non-conjugate GP method for multivariate data that scales linearly with respect to time.

Gaussian Processes Variational Inference

Multi-resolution Multi-task Gaussian Processes

1 code implementation NeurIPS 2019 Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark Girolami

We consider evidence integration from potentially dependent observation processes under varying spatio-temporal sampling resolutions and noise levels.

Gaussian Processes

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