| Implicit Posterior Variational Inference for Deep Gaussian Processes | Haibin YU · Yizhou Chen · Bryan Kian Hsiang Low · Patrick Jaillet · Zhongxiang Dai |
| Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes | Rui Li |
| Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes | Siqi Liu · Milos Hauskrecht |
| Offline Contextual Bayesian Optimization | Ian Char · Youngseog Chung · Willie Neiswanger · Kirthevasan Kandasamy · Oak Nelson · Mark Boyer · Egemen Kolemen · Jeff Schneider |
| Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes | Creighton Heaukulani · Mark van der Wilk |
| Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs | Yusuke Tanaka · Toshiyuki Tanaka · Tomoharu Iwata · Takeshi Kurashima · Maya Okawa · Yasunori Akagi · Hiroyuki Toda |
| Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control | Armin Lederer · Jonas Umlauft · Sandra Hirche |
| Band-Limited Gaussian Processes: The Sinc Kernel | Felipe Tobar |
| Exact Gaussian Processes on a Million Data Points | Ke Wang · Geoff Pleiss · Jacob Gardner · Stephen Tyree · Kilian Weinberger · Andrew Gordon Wilson |
| Function-Space Distributions over Kernels | Gregory Benton · Wesley J Maddox · Jayson Salkey · Julio Albinati · Andrew Gordon Wilson |
| Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes | Lingge Li · Dustin Pluta · Babak Shahbaba · Norbert Fortin · Hernando Ombao · Pierre Baldi |
| Multi-resolution Multi-task Gaussian Processes | Oliver Hamelijnck · Theodoros Damoulas · Kangrui Wang · Mark Girolami |
| Multi-task Learning for Aggregated Data using Gaussian Processes | Fariba Yousefi · Michael T Smith · Mauricio Álvarez |
| Structured Variational Inference in Continuous Cox Process Models | Virginia Aglietti · Edwin Bonilla · Theodoros Damoulas · Sally Cripps |