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Sébastien Marmin
Sébastien Marmin
Docteur en statistique, Laboratoire national de métrologie et d'essais
Verified email at lne.fr - Homepage
Title
Cited by
Cited by
Year
Differentiating the multipoint expected improvement for optimal batch design
S Marmin, C Chevalier, D Ginsbourger
International workshop on machine learning, optimization and big data, 37-48, 2015
672015
Warped gaussian processes and derivative-based sequential designs for functions with heterogeneous variations
S Marmin, D Ginsbourger, J Baccou, J Liandrat
SIAM/ASA Journal on Uncertainty Quantification 6 (3), 991-1018, 2018
312018
Kernel computations from large-scale random features obtained by optical processing units
R Ohana, J Wacker, J Dong, S Marmin, F Krzakala, M Filippone, L Daudet
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
272020
Walsh-hadamard variational inference for bayesian deep learning
S Rossi, S Marmin, M Filippone
Advances in Neural Information Processing Systems 33, 9674-9686, 2020
162020
Deep gaussian processes for calibration of computer models (with discussion)
S Marmin, M Filippone
Bayesian Analysis 17 (4), 1301-1350, 2022
132022
DiceOptim: Kriging-based optimization for computer experiments
V Picheny, D Ginsbourger, O Roustant, M Binois, S Marmin, T Wagner
R package version 2, 2016
132016
Efficient batch-sequential bayesian optimization with moments of truncated gaussian vectors
S Marmin, C Chevalier, D Ginsbourger
arXiv preprint arXiv:1609.02700, 2016
122016
Variational calibration of computer models
S Marmin, M Filippone
arXiv preprint arXiv:1810.12177, 2018
82018
Warping and sampling approaches to non-stationary gaussian process modelling.
S Marmin
Ecole centrale de Marseille, 2017
42017
Developpements pour l’evaluation et la maximisation du critere d’amelioration esperee multipoint en optimisation globale
S Marmin
Master’s thesis, Ecole nationale supérieure des Mines de Saint-Etienne, 2014
42014
Input uncertainty propagation through trained neural networks
P Monchot, L Coquelin, SJ Petit, S Marmin, E Le Pennec, N Fischer
12023
Efficient approximate inference with Walsh-Hadamard variational inference
S Rossi, S Marmin, M Filippone
arXiv preprint arXiv:1912.00015, 2019
12019
Planification adaptative d'expériences numériques par paquets en contexte non stationnaire pour une étude de fissuration mécanique
S Marmin, J Baccou, F Péralès, D Ginsbourger, J Liandrat
CFM 2017-23ème Congrès Français de Mécanique, 2017
12017
Non-parametric warping via local scale estimation for non-stationary Gaussian process modelling
S Marmin, J Baccou, J Liandrat, D Ginsbourger
Wavelets and Sparsity XVII 10394, 413-422, 2017
12017
Processus gaussiens déformés pour l'apprentissage de zones instationnaires
S Marmin, D Ginsbourger, J Baccou, F Perales, J Liandrat
47èmes Journées de Statistique de la SFdS, 2015
12015
The strategic research agenda of the European Metrology Network Mathmet
S Heidenreich, M Bär, C Elster, O Henze, K Lines, S Rhodes, M Cox, ...
ENBIS and EMN Mathmet Joint Workshop Mathematical and Statistical Methods …, 2023
2023
Mathmet Quality Assurance Tools for data, software, and guidelines
K Lines, JL Hippolyte, I George, P Harris, N Fischer, D Gumuchian, ...
ENBIS and EMN Mathmet Joint Workshop Mathematical and Statistical Methods …, 2023
2023
Physiological variability in brain electric conductivity: correcting the effect of the age for the detection of pathological alterations
S Marmin, A Arduino, M Cencini, M Lancione, L Biagi, M Tosetti, L Zilberti
Joint workshop of ENBIS and MATHMET Mathematical and Statistical Methods for …, 2023
2023
Metrological characterisation of quantitative MRI techniques in completely controlled conditions
S Marmin, A Arduino, A Bosnjakovic, L Zilberti
Book of abstracts, 2022
2022
A MATHMET Quality Management System for data and software
K Lines, JL Hippolyte, P Harris, N Fischer, S Marmin, S Ellison, S Cowen, ...
Joint Workshop of ENBIS and MATHMET" Mathematical and Statistical Methods …, 2021
2021
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