2 papers
stat.ML2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Viv Bone, Chris van der Heide, Kieran Mackle +3
Multifidelity models integrate data from multiple sources to produce a single approximator for the underlying process. Dense low-fidelity samples are used to reduce interpolation e…
stat.ML2023
A PAC-Bayesian Perspective on the Interpolating Information Criterion
Liam Hodgkinson, Chris van der Heide, Robert Salomone +2
Deep learning is renowned for its theory-practice gap, whereby principled theory typically fails to provide much beneficial guidance for implementation in practice. This has been h…