62 citations · 178 across the 17 of their papers we have counts for
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stat.AP2021★ 7 cited
Coexchangeable process modelling for uncertainty quantification in joint climate reconstruction
Lachlan Astfalck, Daniel Williamson, Niall Gandy +2
Any experiment with climate models relies on a potentially large set of spatio-temporal boundary conditions. These can represent both the initial state of the system and/or forcing…
stat.ML2021★ 4 cited
Deep Gaussian Process Emulation using Stochastic Imputation
Deyu Ming, Daniel Williamson, Serge Guillas
Deep Gaussian processes (DGPs) provide a rich class of models that can better represent functions with varying regimes or sharp changes, compared to conventional GPs. In this work,…