Biography

I am a third year PhD student at the Alan Turing Institute and the University of Warwick supervised by Theodoros Damoulas. I am part of the London air quality project at the Turing and the Warwick Machine Learning Group.

My research interests lie in Machine Learning and spatio-temporal Statistics with a focus on scalable inference methods for non-parametric Bayesian methods such as Gaussian Processes. I am also interested in multi-fidelity and multi-task modelling, and incorporating structure through non-stationary, non-separable priors and physical laws.

Publications

  • Spatio-Temporal Variational Gaussian Processes
    Oliver Hamelijnck*, William J. Wilkinson*, Niki A. Loppi, Arno Solin, Theodoros Damoulas
    The Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021)
    [paper] [code]
  • Transforming Gaussian processes with normalizing flows
    Juan Maronãs*, Oliver Hamelijnck*, Jeremias Knoblauch, Theodoros Damoulas
    The 24th International Conference on Artificial Intelligence and Statistics (AISTATs 2021)
    [paper] [code]
  • Non-separable Non-stationary random fields
    Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark Steel
    The Thirty-seventh International Conference on Machine Learning (ICML 2020)
    [paper] [code]
  • Multi-resolution Multi-task Gaussian Processes
    Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark Girolami
    The Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019)
    [paper] [code]