David Ginsbourger

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 23

Top Topics

Gaussian Process

Optimization Method

Top Venues

SIAM/ASA J. Uncertain. Quantification

Publications

Cédric Travelletti, Jörg Franke, David Ginsbourger, Stefan Brönnimann
Non-Sequential Ensemble Kalman Filtering using Distributed Arrays. CoRR (2023)
Sam Allen, David Ginsbourger, Johanna Ziegel
Evaluating Forecasts for High-Impact Events Using Transformed Kernel Scores. SIAM/ASA J. Uncertain. Quantification 11 (3) (2023)
Cédric Travelletti, David Ginsbourger, Niklas Linde
Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors. SIAM/ASA J. Uncertain. Quantification 11 (1) (2023)
Johanna Ziegel, David Ginsbourger, Lutz Dümbgen
Characteristic kernels on Hilbert spaces, Banach spaces, and on sets of measures. CoRR (2022)
Eliane Maalouf, David Ginsbourger, Niklas Linde
Fast ABC with Joint Generative Modelling and Subset Simulation. LOD (2021)
Eliane Maalouf, David Ginsbourger, Niklas Linde
Fast ABC with joint generative modelling and subset simulation. CoRR (2021)
Dario Azzimonti, David Ginsbourger, Clément Chevalier, Julien Bect, Yann Richet
Adaptive Design of Experiments for Conservative Estimation of Excursion Sets. Technometrics 63 (1) (2021)
Cédric Travelletti, David Ginsbourger, Niklas Linde
Uncertainty Quantification and Experimental Design for large-scale linear Inverse Problems under Gaussian Process Priors. CoRR (2021)
Clément Chevalier, Olivia Martius, David Ginsbourger
Modeling Nonstationary Extreme Dependence With Stationary Max-Stable Processes and Multidimensional Scaling. J. Comput. Graph. Stat. 30 (3) (2021)
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization. AISTATS (2020)
Trygve Olav Fossum, Cédric Travelletti, Jo Eidsvik, David Ginsbourger, Kanna Rajan
Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling. CoRR (2020)
Mickaël Binois, David Ginsbourger, Olivier Roustant
On the choice of the low-dimensional domain for global optimization via random embeddings. J. Glob. Optim. 76 (1) (2020)
Noémie Jaquier, David Ginsbourger, Sylvain Calinon
Learning from demonstration with model-based Gaussian process. CoRR (2019)
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization. CoRR (2019)
Dario Azzimonti, David Ginsbourger, Jérémy Rohmer, Déborah Idier
Profile Extrema for Visualizing and Quantifying Uncertainties on Excursion Regions: Application to Coastal Flooding. Technometrics 61 (4) (2019)
Noémie Jaquier, David Ginsbourger, Sylvain Calinon
Learning from demonstration with model-based Gaussian process. CoRL (2019)
Sébastien Marmin, David Ginsbourger, Jean Baccou, Jacques Liandrat
Warped Gaussian Processes and Derivative-Based Sequential Designs for Functions with Heterogeneous Variations. SIAM/ASA J. Uncertain. Quantification 6 (3) (2018)
Victor Picheny, David Ginsbourger, Tipaluck Krityakierne
Comment: Some Enhancements Over the Augmented Lagrangian Approach. Technometrics 58 (1) (2016)
Dario Azzimonti, Julien Bect, Clément Chevalier, David Ginsbourger
Quantifying Uncertainties on Excursion Sets Under a Gaussian Random Field Prior. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Tipaluck Krityakierne, David Ginsbourger
Global Optimization with Sparse and Local Gaussian Process Models. MOD (2015)
Mickaël Binois, David Ginsbourger, Olivier Roustant
A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings. LION (2015)
Sébastien Marmin, Clément Chevalier, David Ginsbourger
Differentiating the Multipoint Expected Improvement for Optimal Batch Design. MOD (2015)
Mickaël Binois, David Ginsbourger, Olivier Roustant
Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations. Eur. J. Oper. Res. 243 (2) (2015)
Clément Chevalier, Victor Picheny, David Ginsbourger
KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging. Comput. Stat. Data Anal. 71 (2014)
Victor Picheny, David Ginsbourger
Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. Comput. Stat. Data Anal. 71 (2014)
David Ginsbourger, Jean Baccou, Clément Chevalier, Frédéric Perales, Nicolas Garland, Yann Monerie
Bayesian Adaptive Reconstruction of Profile Optima and Optimizers. SIAM/ASA J. Uncertain. Quantification 2 (1) (2014)
Clément Chevalier, Julien Bect, David Ginsbourger, Emmanuel Vázquez, Victor Picheny, Yann Richet
Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set. Technometrics 56 (4) (2014)
David Ginsbourger, Olivier Roustant, Dominic Schuhmacher, Nicolas Durrande, Nicolas Lenz
On ANOVA Decompositions of Kernels and Gaussian Random Field Paths. MCQMC (2014)
Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin
Rejoinder. Technometrics 55 (1) (2013)
Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin
Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision. Technometrics 55 (1) (2013)
Victor Picheny, David Ginsbourger
A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations. SIAM/ASA J. Uncertain. Quantification 1 (1) (2013)
Clément Chevalier, David Ginsbourger
Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection. LION (2013)
Nicolas Durrande, David Ginsbourger, Olivier Roustant, Laurent Carraro
ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis. J. Multivar. Anal. 115 (2013)
Julien Bect, David Ginsbourger, Ling Li, Victor Picheny, Emmanuel Vázquez
Sequential design of computer experiments for the estimation of a probability of failure. Stat. Comput. 22 (3) (2012)
Mike Preuss, Tobias Wagner, David Ginsbourger
High-Dimensional Model-Based Optimization Based on Noisy Evaluations of Computer Games. LION (2012)
Janis Janusevskis, Rodolphe Le Riche, David Ginsbourger, Ramunas Girdziusas
Expected Improvements for the Asynchronous Parallel Global Optimization of Expensive Functions: Potentials and Challenges. LION (2012)
David Ginsbourger, Céline Helbert, Laurent Carraro
Discrete mixtures of kernels for Kriging-based optimization. Qual. Reliab. Eng. Int. 24 (6) (2008)