Local Gaussian process approximation for large computer experiments

2 March 2013

Papers citing "Local Gaussian process approximation for large computer experiments"

21 / 21 papers shown

Title
Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions Mickael Binois Jeffrey Larson 71 0 0 29 Apr 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 56 13 0 03 Jan 2025
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer Emily C. Hector Amanda Lenzi 36 1 0 31 Dec 2024
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 36 0 0 31 Dec 2024
Posterior Covariance Structures in Gaussian Processes Difeng Cai Edmond Chow Yuanzhe Xi 24 2 0 14 Aug 2024
The inverse Kalman filter X. Fang Mengyang Gu 18 0 0 14 Jul 2024
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio Lyudmila Grigoryeva M. Tamborrino 21 1 0 20 May 2024
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems Jason J. Choi F. Castañeda Wonsuhk Jung Bike Zhang Claire J. Tomlin K. Sreenath 25 3 0 23 Nov 2023
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling Akhil Vakayil Roshan Joseph 15 2 0 17 May 2023
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes Fan Wu Zhanhong Cheng Huiyu Chen T. Qiu Lijun Sun 18 3 0 04 Mar 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation Henry B. Moss Sebastian W. Ober Victor Picheny 22 24 0 24 Jan 2023
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions Frida Viset R. Helmons Manon Kok 15 1 0 17 Oct 2022
Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors Liwei Wang Suraj Yerramilli Akshay Iyer D. Apley Ping Zhu Wei Chen 17 25 0 26 Jun 2021
Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks J. Fuhg M. Marino N. Bouklas 15 59 0 07 May 2021
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms M. Ludkovski 18 7 0 01 Dec 2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains M. Peruzzi Sudipto Banerjee Andrew O. Finley 22 52 0 25 Mar 2020
Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference Leen Alawieh J. Goodman J. Bell 16 4 0 17 Nov 2019
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes Andrew O. Finley A. Datta B. Cook Douglas C. Morton Hans-Erik Andersen Sudipto Banerjee 27 152 0 01 Feb 2017
Practical heteroskedastic Gaussian process modeling for large simulation experiments M. Binois R. Gramacy M. Ludkovski 19 180 0 17 Nov 2016
Speeding up neighborhood search in local Gaussian process prediction R. Gramacy B. Haaland 25 49 0 30 Aug 2014
Massively parallel approximate Gaussian process regression R. Gramacy Jarad Niemi R. Weiss 43 47 0 18 Oct 2013