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Group kernels for Gaussian process metamodels with categorical inputs
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Group kernels for Gaussian process metamodels with categorical inputs

O. Roustant
Esperan Padonou
Yves Deville
Aloïs Clément
G. Perrin
J. Giorla
H. Wynn
ArXiv (abs)PDFHTML

Papers citing "Group kernels for Gaussian process metamodels with categorical inputs"

13 / 13 papers shown
Title
Distributional encoding for Gaussian process regression with qualitative inputs
Sébastien Da Veiga
UQCV
95
0
0
05 Jun 2025
SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration
SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration
M. R
Paul Saves
P. Palar
L. Zuhal
oseph Morlier
MoELRM
82
1
0
25 Mar 2025
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs
Lucas Reding
A. F. López-Lopera
François Bachoc
68
1
0
26 Apr 2024
A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization
A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization
Jiazhao Zhang
Ying Hung
Chung-Ching Lin
Zicheng Liu
116
0
0
19 Jan 2024
Fully Bayesian inference for latent variable Gaussian process models
Fully Bayesian inference for latent variable Gaussian process models
Suraj Yerramilli
Akshay Iyer
Wei Chen
D. Apley
45
3
0
04 Nov 2022
Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters
Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters
M. Moustapha
A. Galimshina
G. Habert
Bruno Sudret
61
10
0
03 Mar 2022
A comparison of mixed-variables Bayesian optimization approaches
A comparison of mixed-variables Bayesian optimization approaches
Jhouben Cuesta Ramirez
Rodolphe Le Riche
O. Roustant
G. Perrin
Cédric Durantin
A. Glière
56
19
0
30 Oct 2021
Bayesian Optimization over Hybrid Spaces
Bayesian Optimization over Hybrid Spaces
Aryan Deshwal
Syrine Belakaria
J. Doppa
72
34
0
08 Jun 2021
A sampling criterion for constrained Bayesian optimization with uncertainties
A sampling criterion for constrained Bayesian optimization with uncertainties
M. R. E. Amri
Rodolphe Le Riche
C. Helbert
Christophette Blanchet-Scalliet
Sébastien Da Veiga
43
14
0
09 Mar 2021
Task-Adaptive Robot Learning from Demonstration with Gaussian Process Models under Replication
Task-Adaptive Robot Learning from Demonstration with Gaussian Process Models under Replication
Miguel Arduengo
Adrià Colomé
J´ulia Borras
Luis Sentis
Carme Torras
32
12
0
15 Oct 2020
Gaussian Process Models with Low-Rank Correlation Matrices for Both Continuous and Categorical Inputs
Gaussian Process Models with Low-Rank Correlation Matrices for Both Continuous and Categorical Inputs
Dominik Kirchhoff
S. Kuhnt
16
3
0
06 Oct 2020
Bayesian optimization of variable-size design space problems
Bayesian optimization of variable-size design space problems
J. Pelamatti
Loïc Brevault
M. Balesdent
El-Ghazali Talbi
Yannick Guerin
80
29
0
06 Mar 2020
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong
D. Ginsbourger
Tipaluck Krityakierne
BDL
88
22
0
09 Oct 2019