65 citations · 220 across the 24 of their papers we have counts for
3 papers · 2 filters
Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics
Arina Odnoblyudova, Çağlar Hizli, ST John +5
In biomedical applications it is often necessary to estimate a physiological response to a treatment consisting of multiple components, and learn the separate effects of the compon…
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…
Practical Equivariances via Relational Conditional Neural Processes
Daolang Huang, Manuel Haussmann, Ulpu Remes +5
Conditional Neural Processes (CNPs) are a class of metalearning models popular for combining the runtime efficiency of amortized inference with reliable uncertainty quantification.…