Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck

23 April 2020

Papers citing "Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck"

5 / 5 papers shown

Title
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 8 0 28 Jan 2023
High-dimensional additive Gaussian processes under monotonicity constraints A. F. López-Lopera François Bachoc O. Roustant 35 9 0 17 May 2022
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy Cole Hawkins Alec Koppel Zheng Zhang 47 4 0 18 Jan 2022
Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication James Di Ehsan Zobeidi Alec Koppel Nikolay Atanasov 28 2 0 12 Oct 2021
Decision-Making Algorithms for Learning and Adaptation with Application to COVID-19 Data S. Maranò Ali H. Sayed 36 6 0 14 Dec 2020