15 citations · 15 across the 2 of their papers we have counts for
3 papers · 1 filter
Convolutional Normalizing Flows for Deep Gaussian Processes
Haibin Yu, Dapeng Liu, Yizhou Chen +2
Deep Gaussian processes (DGPs), a hierarchical composition of GP models, have successfully boosted the expressive power of their single-layer counterpart. However, it is impossible…
Implicit Posterior Variational Inference for Deep Gaussian Processes
Haibin Yu, Yizhou Chen, Zhongxiang Dai +2
A multi-layer deep Gaussian process (DGP) model is a hierarchical composition of GP models with a greater expressive power. Exact DGP inference is intractable, which has motivated…
Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression
Haibin Yu, Trong Nghia Hoang, Kian Hsiang Low +1
This paper presents a novel variational inference framework for deriving a family of Bayesian sparse Gaussian process regression (SGPR) models whose approximations are variationall…