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Local Gaussian process approximation for large computer experiments

Local Gaussian process approximation for large computer experiments

R. Gramacy
D. Apley
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Papers citing "Local Gaussian process approximation for large computer experiments"

19 / 19 papers shown
Title
Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions
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
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
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
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei
Vincent Zhuang
Saraswati Soedarmadji
Yanan Sui
34
0
0
31 Dec 2024
Posterior Covariance Structures in Gaussian Processes
Posterior Covariance Structures in Gaussian Processes
Difeng Cai
Edmond Chow
Yuanzhe Xi
22
2
0
14 Aug 2024
The inverse Kalman filter
The inverse Kalman filter
X. Fang
Mengyang Gu
16
0
0
14 Jul 2024
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers
Guglielmo Gattiglio
Lyudmila Grigoryeva
M. Tamborrino
19
1
0
20 May 2024
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems
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
23
3
0
23 Nov 2023
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling
Akhil Vakayil
Roshan Joseph
13
2
0
17 May 2023
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
Fan Wu
Zhanhong Cheng
Huiyu Chen
T. Qiu
Lijun Sun
16
3
0
04 Mar 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
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
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions
Frida Viset
R. Helmons
Manon Kok
13
1
0
17 Oct 2022
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms
M. Ludkovski
13
7
0
01 Dec 2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
M. Peruzzi
Sudipto Banerjee
Andrew O. Finley
17
52
0
25 Mar 2020
Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference
Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference
Leen Alawieh
J. Goodman
J. Bell
14
4
0
17 Nov 2019
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Andrew O. Finley
A. Datta
B. Cook
Douglas C. Morton
Hans-Erik Andersen
Sudipto Banerjee
25
152
0
01 Feb 2017
Practical heteroskedastic Gaussian process modeling for large simulation experiments
Practical heteroskedastic Gaussian process modeling for large simulation experiments
M. Binois
R. Gramacy
M. Ludkovski
14
180
0
17 Nov 2016
Speeding up neighborhood search in local Gaussian process prediction
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
Massively parallel approximate Gaussian process regression
R. Gramacy
Jarad Niemi
R. Weiss
43
47
0
18 Oct 2013