Papers citing 'Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation'

Title
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow Victor Picheny Joel Berkeley Henry B. Moss Hrvoje Stojić Uri Granta ... Sergio Pascual-Diaz Stratis Markou Jixiang Qing Nasrulloh Loka Ivo Couckuyt 198 22 0 16 Feb 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian OptimisationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Henry B. Moss Sebastian W. Ober Victor Picheny 312 33 0 24 Jan 2023
GAUCHE: A Library for Gaussian Processes in ChemistryNeural Information Processing Systems (NeurIPS), 2022 Ryan-Rhys Griffiths Leo Klarner Henry B. Moss Aditya Ravuri Sang T. Truong ... A. Lee Bingqing Cheng Alán Aspuru-Guzik P. Schwaller Jian Tang GP 327 54 0 06 Dec 2022
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning Paul E. Chang Prakhar Verma S. T. John Victor Picheny Henry B. Moss Arno Solin GP 172 8 0 02 Nov 2022