Sébastien Da Veiga

26 papers A* 1A 4Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based nested kernels. CoRR Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier
2025	J	`jnl`	Distributional encoding for Gaussian process regression with qualitative inputs. CoRR Sébastien Da Veiga
2025	A	`conf`	Learning signals defined on graphs with optimal transport and Gaussian process regression. AISTATS Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber
2025	J	`jnl`	Scalable and adaptive prediction bands with kernel sum-of-squares. CoRR Louis Allain, Sébastien Da Veiga, Brian Staber
2024	A	`conf`	Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels. AISTATS Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber
2024	J	`jnl`	Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels. CoRR Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber
2024	J	`jnl`	Learning signals defined on graphs with optimal transport and Gaussian process regression. CoRR Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber
2023	A*	`conf`	Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization. NeurIPS Clément Bénard, Brian Staber, Sébastien Da Veiga
2022	J	`jnl`	Quantitative performance evaluation of Bayesian neural networks. CoRR Brian Staber, Sébastien Da Veiga
2022	A	`conf`	SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. AISTATS Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2021	A	`conf`	Interpretable Random Forests via Rule Extraction. AISTATS Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2021	J	`jnl`	MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA. CoRR Clément Bénard, Sébastien Da Veiga, Erwan Scornet
2021	J	`jnl`	SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2020	J	`jnl`	Gaussian process regression with linear inequality constraints. Reliab. Eng. Syst. Saf. Sébastien Da Veiga, Amandine Marrel
2020	J	`jnl`	Interpretable Random Forests via Rule Extraction. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2019	—	`conf`	An Adapted Derivative-Free Optimization Method for an Optimal Design Application with Mixed Binary and Continuous Variables. ICCSAMA Thi-Thoi Tran, Delphine Sinoquet, Sébastien Da Veiga, Marcel Mongeau
2019	J	`jnl`	Global Sensitivity Analysis for Optimization with Variable Selection. SIAM/ASA J. Uncertain. Quantification Adrien Spagnol, Rodolphe Le Riche, Sébastien Da Veiga
2019	J	`jnl`	SIRUS: making random forests interpretable. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2018	J	`jnl`	Global sensitivity analysis for optimization with variable selection. CoRR Adrien Spagnol, Rodolphe Le Riche, Sébastien Da Veiga
2018	J	`jnl`	Sequential model aggregation for production forecasting. CoRR Raphaël Deswarte, Véronique Gervais, Gilles Stoltz, Sébastien Da Veiga
2013	J	`jnl`	Appropriate formulation of the objective function for the history matching of seismic attributes. Comput. Geosci. Elodie Tillier, Sébastien Da Veiga, Ratiba Derfoul
2013	J	`jnl`	Global Sensitivity Analysis with Dependence Measures. CoRR Sébastien Da Veiga
2013	J	`jnl`	Image processing tools for better incorporation of 4D seismic data into reservoir models. J. Comput. Appl. Math. Ratiba Derfoul, Sébastien Da Veiga, Christian Gout, Carole Le Guyader, Elodie Tillier
2012	J	`jnl`	Global sensitivity analysis of stochastic computer models with joint metamodels. Stat. Comput. Amandine Marrel, Bertrand Iooss, Sébastien Da Veiga, Mathieu Ribatet
2011	J	`jnl`	Cosimulation as a perturbation method for calibrating porosity and permeability fields to dynamic data. Comput. Geosci. Mickaële Le Ravalec-Dupin, Sébastien Da Veiga
2009	J	`jnl`	Local Polynomial Estimation for Sensitivity Analysis on Models With Correlated Inputs. Technometrics Sébastien Da Veiga, François Wahl, Fabrice Gamboa