← Search

Gia-Lac Tran

2 accepted papers

2021

Sparse within Sparse Gaussian Processes using Neighbor Information

ICML 2021spotlight

Approximations to Gaussian processes (GPs) based on inducing variables, combined with variational inference techniques, enable state-of-the-art sparse approaches to infer GPs at scale through mini-batch based learning. In this work, we further push the limits of scalability of sparse GPs by allowing…

Cited by 21SourcePDFScholar
2019

Calibrating Deep Convolutional Gaussian Processes

AISTATS 2019poster

The wide adoption of Convolutional Neural Networks CNNs in applications where decision-making under uncertainty is fundamental, has brought a great deal of attention to the ability of these models to accurately quantify the uncertainty in their predictions. Previous work on combining CNNs with Gauss…

Cited by 54SourcePDFScholar