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Recursive co-kriging model for Design of Computer experiments with
  multiple levels of fidelity with an application to hydrodynamic
v1v2v3 (latest)

Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic

2 October 2012
Loic Le Gratiet
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic"

50 / 61 papers shown
Assessing the performance of correlation-based multi-fidelity neural emulators
Assessing the performance of correlation-based multi-fidelity neural emulators
Cristian J. Villatoro
Gianluca Geraci
Daniele E. Schiavazzi
178
1
0
02 Dec 2025
Multi-level informed optimization via decomposed Kriging for large design problems under uncertainty
Multi-level informed optimization via decomposed Kriging for large design problems under uncertainty
Enrico Ampellio
B. Gjorgiev
G. Sansavini
AI4CE
203
0
0
09 Oct 2025
Projection-based multifidelity linear regression for data-scarce applications
Projection-based multifidelity linear regression for data-scarce applications
Vignesh Sella
Julie Pham
Karen E. Willcox
Anirban Chaudhuri
103
0
0
11 Aug 2025
On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
Arjun Manoj
Anastasia S. Georgiou
Dimitris G. Giovanis
T. Sapsis
Ioannis G. Kevrekidis
253
0
0
01 Aug 2025
Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment
Yongpeng Zhao
Maik Pfefferkorn
Maximilian Templer
R. Findeisen
211
1
0
10 Jun 2025
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators
Xinming Wang
Simon Mak
John Joshua Miller
Jianguo Wu
353
2
0
16 Oct 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy SearchIEEE Transactions on Signal Processing (IEEE TSP), 2024
Yunchuan Zhang
Sangwoo Park
Osvaldo Simeone
587
10
0
14 Mar 2024
Multifidelity linear regression for scientific machine learning from
  scarce data
Multifidelity linear regression for scientific machine learning from scarce dataFoundations of Data Science (FDS), 2024
Elizabeth Qian
Dayoung Kang
Vignesh Sella
Anirban Chaudhuri
AI4CE
324
6
0
13 Mar 2024
Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning
Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planningThe international journal of robotics research (IJRR), 2024
Gilhyun Ryou
Geoffrey Wang
S. Karaman
452
4
0
13 Mar 2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Viv Bone
Chris van der Heide
Kieran Mackle
Ingo Jahn
P. Dower
Chris Manzie
245
3
0
25 Feb 2024
Sparse discovery of differential equations based on multi-fidelity
  Gaussian process
Sparse discovery of differential equations based on multi-fidelity Gaussian processJournal of Computational Physics (JCP), 2024
Yuhuang Meng
Yue Qiu
418
2
0
22 Jan 2024
A Bayesian neural network approach to Multi-fidelity surrogate modelling
A Bayesian neural network approach to Multi-fidelity surrogate modellingInternational Journal for Uncertainty Quantification (IJUQ), 2023
Baptiste Kerleguer
C. Cannamela
Josselin Garnier
UQCV
204
7
0
05 Dec 2023
Epistemic Modeling Uncertainty of Rapid Neural Network Ensembles for
  Adaptive Learning
Epistemic Modeling Uncertainty of Rapid Neural Network Ensembles for Adaptive LearningFinite elements in analysis and design (FEAD), 2023
Atticus Beachy
Harok Bae
José Camberos
R. Grandhi
224
5
0
12 Sep 2023
Physics-informed reinforcement learning via probabilistic co-adjustment
  functions
Physics-informed reinforcement learning via probabilistic co-adjustment functions
Nat Wannawas
A. Faisal
AI4CE
140
0
0
11 Sep 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning
Disentangled Multi-Fidelity Deep Bayesian Active LearningInternational Conference on Machine Learning (ICML), 2023
D. Wu
Ruijia Niu
Matteo Chinazzi
Yi-An Ma
Rose Yu
AI4CE
390
15
0
07 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design
  and Health Prognostics: A Tutorial
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A TutorialMechanical systems and signal processing (MSSP), 2023
V. Nemani
Luca Biggio
Xun Huan
Zhen Hu
Olga Fink
Anh Tran
Yan Wang
Xiaoge Zhang
Chao Hu
AI4CE
325
151
0
07 May 2023
Recursive Nearest Neighbor Co-Kriging Models for Big Multiple Fidelity
  Spatial Data Sets
Recursive Nearest Neighbor Co-Kriging Models for Big Multiple Fidelity Spatial Data Sets
Si Cheng
B. Konomi
Georgios Karagiannis
Emily L. Kang
BDL
188
1
0
26 Feb 2023
Multi-fidelity surrogate modeling for temperature field prediction using
  deep convolution neural network
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural networkEngineering applications of artificial intelligence (Eng. Appl. Artif. Intell.), 2023
Yunyang Zhang
Zhiqiang Gong
Weien Zhou
Xiaoyu Zhao
Xiaohu Zheng
Wen Yao
AI4CE
172
35
0
17 Jan 2023
Falsification of Learning-Based Controllers through Multi-Fidelity
  Bayesian Optimization
Falsification of Learning-Based Controllers through Multi-Fidelity Bayesian OptimizationEuropean Control Conference (ECC), 2022
Zahra Shahrooei
Mykel J. Kochenderfer
Ali Baheri
285
10
0
28 Dec 2022
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian
  Optimization
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian OptimizationComputers and Chemical Engineering (CCE), 2022
Jose Pablo Folch
Robert M. Lee
B. Shafei
David Walz
Calvin Tsay
Mark van der Wilk
Ruth Misener
363
36
0
11 Nov 2022
Multi-fidelity Hierarchical Neural Processes
Multi-fidelity Hierarchical Neural ProcessesKnowledge Discovery and Data Mining (KDD), 2022
D. Wu
Matteo Chinazzi
Alessandro Vespignani
Yi-An Ma
Rose Yu
AI4CE
213
20
0
10 Jun 2022
Recent Advances in Bayesian Optimization
Recent Advances in Bayesian OptimizationACM Computing Surveys (ACM CSUR), 2022
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
415
482
0
07 Jun 2022
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian
  Optimization
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization
Gilhyun Ryou
E. Tal
S. Karaman
209
7
0
01 Jun 2022
RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction
  for High-dimensional Uncertainty Quantification
RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification
Jiahao Zhang
Shiqi Zhang
Guang Lin
168
0
0
11 Apr 2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains
Haitao Liu
Kai Wu
Yew-Soon Ong
Chao Bian
Xiaomo Jiang
Xiaofang Wang
341
15
0
25 Feb 2022
Control Variate Polynomial Chaos: Optimal Fusion of Sampling and
  Surrogates for Multifidelity Uncertainty Quantification
Control Variate Polynomial Chaos: Optimal Fusion of Sampling and Surrogates for Multifidelity Uncertainty QuantificationInternational Journal for Uncertainty Quantification (IJUQ), 2022
Hang Yang
Y. Fujii
K. W. Wang
Alex A. Gorodetsky
213
6
0
26 Jan 2022
Transfer Learning with Gaussian Processes for Bayesian Optimization
Transfer Learning with Gaussian Processes for Bayesian OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Petru Tighineanu
Kathrin Skubch
P. Baireuther
Attila Reiss
Felix Berkenkamp
Julia Vinogradska
232
44
0
22 Nov 2021
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes
Safe Real-Time Optimization using Multi-Fidelity Gaussian ProcessesIEEE Conference on Decision and Control (CDC), 2021
Panagiotis Petsagkourakis
Benoît Chachuat
Ehecatl Antonio del Rio Chanona
173
8
0
10 Nov 2021
Prediction of liquid fuel properties using machine learning models with
  Gaussian processes and probabilistic conditional generative learning
Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning
Rodolfo S. M. Freitas
Ágatha P. F. Lima
Cheng Chen
F. Rochinha
D. Mira
Xi Jiang
255
0
0
18 Oct 2021
Multi-fidelity surrogate modeling for time-series outputs
Multi-fidelity surrogate modeling for time-series outputs
Baptiste Kerleguer
196
5
0
23 Sep 2021
Physics-integrated hybrid framework for model form error identification
  in nonlinear dynamical systems
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systemsMechanical systems and signal processing (MSSP), 2021
Shailesh Garg
S. Chakraborty
B. Hazra
186
26
0
01 Sep 2021
Physics-informed CoKriging model of a redox flow battery
Physics-informed CoKriging model of a redox flow battery
Amanda A. Howard
A. Tartakovsky
111
16
0
17 Jun 2021
Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty
  Quantification
Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty QuantificationComputational Mechanics (CM), 2021
F. Newberry
Jerrad Hampton
K. Jansen
Alireza Doostan
206
6
0
15 Apr 2021
GIBBON: General-purpose Information-Based Bayesian OptimisatioN
GIBBON: General-purpose Information-Based Bayesian OptimisatioNJournal of machine learning research (JMLR), 2021
Henry B. Moss
David S. Leslie
Javier I. González
Paul Rayson
217
55
0
05 Feb 2021
Augmented Gaussian Random Field: Theory and Computation
Augmented Gaussian Random Field: Theory and ComputationDiscrete and Continuous Dynamical Systems. Series A (DCDS-A), 2020
S. Zhang
Xiu Yang
S. Tindel
Guang Lin
180
3
0
03 Sep 2020
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian
  Processes
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes
Panagiotis Tsilifis
Piyush Pandita
Sayan Ghosh
Valeria Andreoli
T. Vandeputte
Liping Wang
321
20
0
05 Aug 2020
Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process
  Regression
Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression
Yixiang Deng
Guang Lin
Xiu Yang
155
9
0
03 Aug 2020
MFNets: Data efficient all-at-once learning of multifidelity surrogates
  as directed networks of information sources
MFNets: Data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources
Alex Gorodetsky
J. Jakeman
Gianluca Geraci
AI4CE
226
29
0
03 Aug 2020
Sequential design of multi-fidelity computer experiments: maximizing the
  rate of stepwise uncertainty reduction
Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction
Rémi Stroh
Julien Bect
S. Demeyer
N. Fischer
Damien Marquis
E. Vázquez
288
17
0
27 Jul 2020
Resource Aware Multifidelity Active Learning for Efficient Optimization
Resource Aware Multifidelity Active Learning for Efficient Optimization
Francesco Grassi
Giorgio Manganini
Michele Garraffa
L. Mainini
181
6
0
09 Jul 2020
Overview of Gaussian process based multi-fidelity techniques with
  variable relationship between fidelities
Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities
Loïc Brevault
M. Balesdent
Ali Hebbal
229
91
0
30 Jun 2020
Multi-fidelity modeling with different input domain definitions using
  Deep Gaussian Processes
Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes
Ali Hebbal
Loïc Brevault
M. Balesdent
El-Ghazali Talbi
N. Melab
AI4CE
236
43
0
29 Jun 2020
Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor
  Maneuvers
Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers
Gilhyun Ryou
E. Tal
S. Karaman
280
47
0
03 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural
  network
Transfer learning based multi-fidelity physics informed deep neural network
S. Chakraborty
PINNOODAI4CE
391
210
0
19 May 2020
Efficient Characterization of Dynamic Response Variation Using
  Multi-Fidelity Data Fusion through Composite Neural Network
Efficient Characterization of Dynamic Response Variation Using Multi-Fidelity Data Fusion through Composite Neural Network
K. Zhou
Jiong Tang
AI4CE
292
23
0
07 May 2020
On transfer learning of neural networks using bi-fidelity data for
  uncertainty propagation
On transfer learning of neural networks using bi-fidelity data for uncertainty propagationInternational Journal for Uncertainty Quantification (IJUQ), 2020
Subhayan De
Jolene Britton
Matthew J. Reynolds
Ryan W. Skinner
Kenneth Jansen
Alireza Doostan
224
56
0
11 Feb 2020
Objective Bayesian Analysis of a Cokriging Model for Hierarchical
  Multifidelity Codes
Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes
P. Ma
176
9
0
22 Oct 2019
Multi-fidelity classification using Gaussian processes: accelerating the
  prediction of large-scale computational models
Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational modelsComputer Methods in Applied Mechanics and Engineering (CMAME), 2019
F. Sahli Costabal
P. Perdikaris
E. Kuhl
D. Hurtado
AI4CE
167
53
0
09 May 2019
Active Multi-Information Source Bayesian Quadrature
Active Multi-Information Source Bayesian Quadrature
A. Gessner
Javier I. González
Maren Mahsereci
296
32
0
27 Mar 2019
Deep Gaussian Processes for Multi-fidelity Modeling
Deep Gaussian Processes for Multi-fidelity Modeling
Kurt Cutajar
Mark Pullin
Andreas C. Damianou
Neil D. Lawrence
Javier I. González
AI4CE
250
124
0
18 Mar 2019
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