François Bachoc

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 41

Top Topics

Gaussian Process

Top Venues

SIAM/ASA J. Uncertain. Quantification

J. Multivar. Anal.

Publications

François Bachoc, Tommaso Cesari, Roberto Colomboni
A Contextual Online Learning Theory of Brokerage. CoRR (2024)
Joachim Bona-Pellissier, François Malgouyres, François Bachoc
Geometry-induced Implicit Regularization in Deep ReLU Neural Networks. CoRR (2024)
François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
Fair Online Bilateral Trade. CoRR (2024)
Julien Demange-Chryst, François Bachoc, Jérôme Morio, Timothé Krauth
Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling. Trans. Mach. Learn. Res. 2024 (2024)
José Betancourt, François Bachoc, Thierry Klein, Déborah Idier, Jérémy Rohmer, Yves Deville
Package for Gaussian Process Regression with Scalar and Functional Inputs. J. Stat. Softw. 109 (5) (2024)
Julien Demange-Chryst, François Bachoc, Jérôme Morio, Timothé Krauth
Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling. CoRR (2023)
François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS (2023)
Julien Demange-Chryst, François Bachoc, Jérôme Morio
Efficient estimation of multiple expectations with the same sample by adaptive importance sampling and control variates. Stat. Comput. 33 (5) (2023)
Joachim Bona-Pellissier, François Bachoc, François Malgouyres
Parameter identifiability of a deep feedforward ReLU neural network. Mach. Learn. 112 (11) (2023)
Andrés F. López-Lopera, Déborah Idier, Jérémy Rohmer, François Bachoc
Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment. Reliab. Eng. Syst. Saf. 218 (Part) (2022)
Joachim Bona-Pellissier, François Malgouyres, François Bachoc
Local Identifiability of Deep ReLU Neural Networks: the Theory. NeurIPS (2022)
Andrés F. López-Lopera, François Bachoc, Olivier Roustant
High-dimensional additive Gaussian processes under monotonicity constraints. CoRR (2022)
François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR (2022)
Baptiste Broto, François Bachoc, Laura Clouvel, Jean-Marc Martinez
Block-Diagonal Covariance Estimation and Application to the Shapley Effects in Sensitivity Analysis. SIAM/ASA J. Uncertain. Quantification 10 (1) (2022)
François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice
A Near-Optimal Algorithm for Univariate Zeroth-Order Budget Convex Optimization. CoRR (2022)
Andrés F. López-Lopera, François Bachoc, Olivier Roustant
High-dimensional Additive Gaussian Processes under Monotonicity Constraints. NeurIPS (2022)
François Bachoc, Andrés F. López-Lopera, Olivier Roustant
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints. SIAM J. Math. Data Sci. 4 (2) (2022)
François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice
Regret Analysis of Dyadic Search. CoRR (2022)
François Bachoc, Tommaso Renato Cesari, Sébastien Gerchinovitz
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. CoRR (2021)
Anis Fradi, Y. Feunteun, Chafik Samir, M. Baklouti, François Bachoc, Jean-Michel Loubes
Bayesian regression and classification using Gaussian process priors indexed by probability density functions. Inf. Sci. 548 (2021)
François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. NeurIPS (2021)
François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz
The Sample Complexity of Level Set Approximation. AISTATS (2021)
Baptiste Broto, François Bachoc, Marine Depecker, Jean-Marc Martinez
Gaussian Linear Approximation for the Estimation of the Shapley Effects. SIAM/ASA J. Uncertain. Quantification 9 (3) (2021)
José Betancourt, François Bachoc, Thierry Klein, Déborah Idier, Rodrigo Pedreros, Jérémy Rohmer
Gaussian process metamodeling of functional-input code for coastal flood hazard assessment. Reliab. Eng. Syst. Saf. 198 (2020)
François Bachoc, Céline Helbert, Victor Picheny
Gaussian process optimization with failures: classification and convergence proof. J. Glob. Optim. 78 (3) (2020)
Baptiste Broto, François Bachoc, Marine Depecker
Variance Reduction for Estimation of Shapley Effects and Adaptation to Unknown Input Distribution. SIAM/ASA J. Uncertain. Quantification 8 (2) (2020)
Andrés F. López-Lopera, Déborah Idier, Jérémy Rohmer, François Bachoc
Multi-Output Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard Assessment. CoRR (2020)
Chafik Samir, Jean-Michel Loubes, Anne-Françoise Yao, François Bachoc
Learning a Gaussian Process Model on the Riemannian Manifold of Non-decreasing Distribution Functions. PRICAI (2) (2019)
François Bachoc, Moreno Bevilacqua, Daira Velandia
Composite likelihood estimation for a Gaussian process under fixed domain asymptotics. J. Multivar. Anal. 174 (2019)
Baptiste Broto, François Bachoc, Marine Depecker, Jean-Marc Martinez
Sensitivity indices for independent groups of variables. Math. Comput. Simul. 163 (2019)
Mai Trang Vu, François Bachoc, Edouard Pauwels
Rate of convergence for geometric inference based on the empirical Christoffel function. CoRR (2019)
Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC. CoRR (2019)
Malek Ben Salem, François Bachoc, Olivier Roustant, Fabrice Gamboa, Lionel Tomaso
Gaussian Process-Based Dimension Reduction for Goal-Oriented Sequential Design. SIAM/ASA J. Uncertain. Quantification 7 (4) (2019)
François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Nil Venet
A Gaussian Process Regression Model for Distribution Inputs. IEEE Trans. Inf. Theory 64 (10) (2018)
Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints. SIAM/ASA J. Uncertain. Quantification 6 (3) (2018)
François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Laurent Risser
Entropic Variable Boosting for Explainability and Interpretability in Machine Learning. CoRR (2018)
Didier Rullière, Nicolas Durrande, François Bachoc, Clément Chevalier
Nested Kriging predictions for datasets with a large number of observations. Stat. Comput. 28 (4) (2018)
Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
Finite-dimensional Gaussian approximation with linear inequality constraints. CoRR (2017)
François Bachoc, Agnès Lagnoux, Thi Mong Ngoc Nguyen
Cross-validation estimation of covariance parameters under fixed-domain asymptotics. J. Multivar. Anal. 160 (2017)
François Bachoc, Martin Ehler, Manuel Gräf
Optimal configurations of lines and a statistical application. Adv. Comput. Math. 43 (1) (2017)
Reinhard Furrer, François Bachoc, Juan Du
Asymptotic properties of multivariate tapering for estimation and prediction. J. Multivar. Anal. 149 (2016)
François Bachoc
Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes. J. Multivar. Anal. 125 (2014)
François Bachoc
Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification. Comput. Stat. Data Anal. 66 (2013)