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Sébastien Da Veiga
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2020 – today
- 2024
- [c5]Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber:
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels. AISTATS 2024: 1297-1305 - [i10]Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber:
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels. CoRR abs/2402.03838 (2024) - [i9]Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber:
Learning signals defined on graphs with optimal transport and Gaussian process regression. CoRR abs/2410.15721 (2024) - 2023
- [c4]Clément Bénard, Brian Staber, Sébastien Da Veiga:
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization. NeurIPS 2023 - 2022
- [c3]Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet:
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. AISTATS 2022: 5563-5582 - [i8]Brian Staber, Sébastien Da Veiga:
Quantitative performance evaluation of Bayesian neural networks. CoRR abs/2206.06779 (2022) - 2021
- [c2]Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet:
Interpretable Random Forests via Rule Extraction. AISTATS 2021: 937-945 - [i7]Clément Bénard, Sébastien Da Veiga, Erwan Scornet:
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA. CoRR abs/2102.13347 (2021) - [i6]Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet:
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. CoRR abs/2105.11724 (2021) - 2020
- [j7]Sébastien Da Veiga, Amandine Marrel:
Gaussian process regression with linear inequality constraints. Reliab. Eng. Syst. Saf. 195: 106732 (2020) - [i5]Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet:
Interpretable Random Forests via Rule Extraction. CoRR abs/2004.14841 (2020)
2010 – 2019
- 2019
- [j6]Adrien Spagnol, Rodolphe Le Riche
, Sébastien Da Veiga:
Global Sensitivity Analysis for Optimization with Variable Selection. SIAM/ASA J. Uncertain. Quantification 7(2): 417-443 (2019) - [c1]Thi-Thoi Tran, Delphine Sinoquet
An Adapted Derivative-Free Optimization Method for an Optimal Design Application with Mixed Binary and Continuous Variables. ICCSAMA 2019: 88-98 - [i4]Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet:
SIRUS: making random forests interpretable. CoRR abs/1908.06852 (2019) - 2018
- [i3]Adrien Spagnol, Rodolphe Le Riche, Sébastien Da Veiga:
Global sensitivity analysis for optimization with variable selection. CoRR abs/1811.04646 (2018) - [i2]Raphaël Deswarte, Véronique Gervais, Gilles Stoltz, Sébastien Da Veiga:
Sequential model aggregation for production forecasting. CoRR abs/1812.10389 (2018) - 2013
- [j5]Elodie Tillier, Sébastien Da Veiga, Ratiba Derfoul:
Appropriate formulation of the objective function for the history matching of seismic attributes. Comput. Geosci. 51: 64-73 (2013) - [j4]Ratiba Derfoul, Sébastien Da Veiga, Christian Gout
Image processing tools for better incorporation of 4D seismic data into reservoir models. J. Comput. Appl. Math. 240: 111-122 (2013) - [i1]Sébastien Da Veiga:
Global Sensitivity Analysis with Dependence Measures. CoRR abs/1311.2483 (2013) - 2012
- [j3]Amandine Marrel
Global sensitivity analysis of stochastic computer models with joint metamodels. Stat. Comput. 22(3): 833-847 (2012) - 2011
- [j2]Mickaële Le Ravalec-Dupin
Cosimulation as a perturbation method for calibrating porosity and permeability fields to dynamic data. Comput. Geosci. 37(9): 1400-1412 (2011)
2000 – 2009
- 2009
- [j1]Sébastien Da Veiga, François Wahl, Fabrice Gamboa:
Local Polynomial Estimation for Sensitivity Analysis on Models With Correlated Inputs. Technometrics 51(4): 452-463 (2009)
Coauthor Index
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