Nicolas Durrande
Nicolas Durrande
Director of Research at Secondmind
Adresse e-mail validée de secondmind.ai - Page d'accueil
Titre
Citée par
Citée par
Année
Variational Fourier Features for Gaussian Processes.
J Hensman, N Durrande, A Solin
J. Mach. Learn. Res. 18 (151–1), 2017
1092017
Additive covariance kernels for high-dimensional Gaussian process modeling
N Durrande, D Ginsbourger, O Roustant
Annales de la Faculté des sciences de Toulouse: Mathématiques 21 (3), 481-499, 2012
97*2012
ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis
N Durrande, D Ginsbourger, O Roustant, L Carraro
Journal of Multivariate Analysis 115, 57-67, 2013
692013
Finite-dimensional Gaussian approximation with linear inequality constraints
AF López-Lopera, F Bachoc, N Durrande, O Roustant
SIAM/ASA Journal on Uncertainty Quantification 6 (3), 1224-1255, 2018
392018
Distance-based kriging relying on proxy simulations for inverse conditioning
D Ginsbourger, B Rosspopoff, G Pirot, N Durrande, P Renard
Advances in water resources 52, 275-291, 2013
382013
Nested Kriging predictions for datasets with a large number of observations
D Rullière, N Durrande, F Bachoc, C Chevalier
Statistics and Computing 28 (4), 849-867, 2018
342018
Detecting periodicities with Gaussian processes
N Durrande, J Hensman, M Rattray, ND Lawrence
PeerJ Computer Science 2, e50, 2016
33*2016
An analytic comparison of regularization methods for Gaussian processes
H Mohammadi, RL Riche, N Durrande, E Touboul, X Bay
arXiv preprint arXiv:1602.00853, 2016
212016
Banded matrix operators for Gaussian Markov models in the automatic differentiation era
N Durrande, V Adam, L Bordeaux, S Eleftheriadis, J Hensman
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
172019
On ANOVA decompositions of kernels and Gaussian random field paths
D Ginsbourger, O Roustant, D Schuhmacher, N Durrande, N Lenz
Monte Carlo and Quasi-Monte Carlo Methods, 315-330, 2016
172016
Etude de classes de noyaux adaptées à la simplification et à l’interprétation des modeles d’approximation. Une approche fonctionnelle et probabiliste.
N Durrande
Ph. D. thesis, Saint-Etienne, EMSE, 2011
172011
On degeneracy and invariances of random fields paths with applications in Gaussian process modelling
D Ginsbourger, O Roustant, N Durrande
Journal of statistical planning and inference 170, 117-128, 2016
162016
Damage localisation in delaminated composite plates using a Gaussian process approach
N Corrado, M Gherlone, C Surace, J Hensman, N Durrande
Meccanica 50 (10), 2537-2546, 2015
132015
Kernels and designs for modelling invariant functions: From group invariance to additivity
D Ginsbourger, N Durrande, O Roustant
mODa 10–Advances in Model-Oriented Design and Analysis, 107-115, 2013
122013
Single and multiple crack localization in beam-like structures using a Gaussian process regression approach
N Corrado, N Durrande, M Gherlone, J Hensman, M Mattone, C Surace
Journal of Vibration and Control 24 (18), 4160-4175, 2018
112018
Invariances of random fields paths, with applications in Gaussian process regression
D Ginsbourger, O Roustant, N Durrande
arXiv preprint arXiv:1308.1359, 2013
102013
Gaussian process modulated cox processes under linear inequality constraints
AF López-Lopera, ST John, N Durrande
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
92019
Sparse Gaussian processes with spherical harmonic features
V Dutordoir, N Durrande, J Hensman
International Conference on Machine Learning, 2793-2802, 2020
82020
Doubly sparse variational Gaussian processes
V Adam, S Eleftheriadis, A Artemev, N Durrande, J Hensman
International Conference on Artificial Intelligence and Statistics, 2874-2884, 2020
62020
Some properties of nested Kriging predictors
F Bachoc, N Durrande, D Rullière, C Chevalier
arXiv preprint arXiv:1707.05708, 2017
62017
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20