1 citations · 2 across the 5 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
stat.ML2023
Thin and Deep Gaussian Processes
Daniel Augusto de Souza, Alexander Nikitin, ST John +6
Gaussian processes (GPs) can provide a principled approach to uncertainty quantification with easy-to-interpret kernel hyperparameters, such as the lengthscale, which controls the…
stat.ML2023
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes
Magnus Ross, Markus Heinonen
Hamiltonian mechanics is one of the cornerstones of natural sciences. Recently there has been significant interest in learning Hamiltonian systems in a free-form way directly from…