Local Gaussian process approximation for large computer experiments

2 March 2013

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

39 / 39 papers shown

Title
Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions Mickael Binois Jeffrey Larson 74 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 68 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 41 1 0 31 Dec 2024
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 132 0 0 31 Dec 2024
Posterior Covariance Structures in Gaussian Processes Difeng Cai Edmond Chow Yuanzhe Xi 37 2 0 14 Aug 2024
The inverse Kalman filter X. Fang Mengyang Gu 29 0 0 14 Jul 2024
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio Lyudmila Grigoryeva M. Tamborrino 32 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 35 3 0 23 Nov 2023
Minibatch Markov chain Monte Carlo Algorithms for Fitting Gaussian Processes Matthew J. Heaton Jacob A. Johnson 8 1 0 26 Oct 2023
Privacy-aware Gaussian Process Regression Rui Tuo R. Bhattacharya 6 1 0 25 May 2023
Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data Saumajit Saha J. Bradley 19 5 0 22 May 2023
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling Akhil Vakayil Roshan Joseph 23 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 27 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 32 24 0 24 Jan 2023
Active Learning of Piecewise Gaussian Process Surrogates Chiwoo Park R. Waelder Bonggwon Kang Benji Maruyama Soondo Hong R. Gramacy GP 19 1 0 20 Jan 2023
Locally Smoothed Gaussian Process Regression Davit Gogolashvili B. Kozyrskiy Maurizio Filippone 14 8 0 18 Oct 2022
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions Frida Viset R. Helmons Manon Kok 31 1 0 17 Oct 2022
Optimal Sensor Placement in Body Surface Networks using Gaussian Processes Emad Alenany Changqing Cheng 11 0 0 07 Sep 2022
Non-smooth Bayesian Optimization in Tuning Problems Hengrui Luo J. Demmel Younghyun Cho Xin Li Yang Liu 17 13 0 15 Sep 2021
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 35 25 0 26 Jun 2021
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 26 5 0 04 Jun 2021
Scalable Cross Validation Losses for Gaussian Process Models M. Jankowiak Geoff Pleiss 15 6 0 24 May 2021
Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks J. Fuhg M. Marino N. Bouklas 28 59 0 07 May 2021
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms M. Ludkovski 28 7 0 01 Dec 2020
KrigHedge: Gaussian Process Surrogates for Delta Hedging M. Ludkovski Yuri F. Saporito 35 5 0 16 Oct 2020
Scaled Vecchia approximation for fast computer-model emulation Matthias Katzfuss J. Guinness E. Lawrence 14 40 0 01 May 2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains M. Peruzzi Sudipto Banerjee Andrew O. Finley 30 51 0 25 Mar 2020
Deep Gaussian Markov Random Fields Per Sidén Fredrik Lindsten BDL 14 22 0 18 Feb 2020
Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments P. Ma Anirban Mondal B. Konomi J. Hobbs J. Song E. Kang 15 13 0 21 Nov 2019
Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference Leen Alawieh J. Goodman J. Bell 33 4 0 17 Nov 2019
Bayesian inference and non-linear extensions of the CIRCE method for quantifying the uncertainty of closure relationships integrated into thermal-hydraulic system codes Guillaume Damblin P. Gaillard 14 20 0 13 Feb 2019
Towards a Complete Picture of Stationary Covariance Functions on Spheres Cross Time P. White Emilio Porcu 15 8 0 11 Jul 2018
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes Andrew O. Finley A. Datta B. Cook Douglas C. Morton Hans-Erik Andersen Sudipto Banerjee 35 152 0 01 Feb 2017
Practical heteroskedastic Gaussian process modeling for large simulation experiments M. Binois R. Gramacy M. Ludkovski 27 181 0 17 Nov 2016
Permutation and Grouping Methods for Sharpening Gaussian Process Approximations J. Guinness 10 148 0 17 Sep 2016
Asymptotic analysis of covariance parameter estimation for Gaussian processes in the misspecified case F. Bachoc 18 31 0 05 Dec 2014
Speeding up neighborhood search in local Gaussian process prediction R. Gramacy B. Haaland 35 49 0 30 Aug 2014
A general decision framework for structuring computation using Data Directional Scaling to process massive similarity matrices Daniel J. Lawson N. Adams 38 4 0 17 Mar 2014
Massively parallel approximate Gaussian process regression R. Gramacy Jarad Niemi R. Weiss 56 47 0 18 Oct 2013