Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation

24 January 2023

Papers citing "Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation"

21 / 21 papers shown

Title
Koopman-Equivariant Gaussian Processes Petar Bevanda Max Beier Armin Lederer A. Capone Stefan Sosnowski Sandra Hirche AI4TS 58 1 0 10 Feb 2025
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies from Simulated Nonparametric Functions Cen Li Marc Toussaint Barbara Rakitsch Christoph Zimmer OffRL 58 0 0 26 Jan 2025
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 34 0 0 31 Dec 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal Juliusz Ziomek Masaki Adachi Michael A. Osborne 14 1 0 14 Oct 2024
SCORE: A 1D Reparameterization Technique to Break Bayesian Optimization's Curse of Dimensionality Joseph Chakar 19 0 0 18 Jun 2024
Approximation-Aware Bayesian Optimization N. Maus Kyurae Kim Geoff Pleiss David Eriksson John P. Cunningham Jacob R. Gardner 19 1 0 06 Jun 2024
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization Anthony Bardou Patrick Thiran Giovanni Ranieri 19 1 0 23 May 2024
No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes Minbiao Han Fengxue Zhang Yuxin Chen 24 2 0 14 May 2024
COMO: Compact Mapping and Odometry Eric Dexheimer Andrew J. Davison 21 3 0 04 Apr 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 31 1 0 22 Feb 2024
Motion Code: Robust Time series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning Chandrajit L. Bajaj Minh Nguyen AI4TS 22 0 0 21 Feb 2024
Combining additivity and active subspaces for high-dimensional Gaussian process modeling M. Binois Victor Picheny 14 0 0 06 Feb 2024
Sparse Variational Student-t Processes Jian Xu Delu Zeng 11 1 0 09 Dec 2023
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation Fengxue Zhang Jialin Song James Bowden Alexander Ladd Yisong Yue Thomas A. Desautels Yuxin Chen 25 6 0 25 Jul 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning Adam X. Yang Laurence Aitchison Henry B. Moss 6 4 0 22 Feb 2023
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 10 13 0 16 Feb 2023
GAUCHE: A Library for Gaussian Processes in Chemistry 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 13 40 0 06 Dec 2022
Local Function Complexity for Active Learning via Mixture of Gaussian Processes Danny Panknin Stefan Chmiela Klaus-Robert Muller Shinichi Nakajima 16 0 0 27 Feb 2019
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 357 0 06 Mar 2017
Local Gaussian process approximation for large computer experiments R. Gramacy D. Apley 84 391 0 02 Mar 2013
Determinantal point processes for machine learning Alex Kulesza B. Taskar 146 1,045 0 25 Jul 2012