Mickaël Binois

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 25

Top Topics

Gaussian Process

Stochastic Process

Top Venues

J. Glob. Optim.

ACM Trans. Evol. Learn. Optim.

Publications

Khadija Musayeva, Mickaël Binois
Shared active subspace for multivariate vector-valued functions. CoRR (2024)
Khadija Musayeva, Mickaël Binois
Improved Multi-label Propagation for Small Data with Multi-objective Optimization. ECML/PKDD (4) (2023)
Arindam Fadikar, Nicholson T. Collier, Abby Stevens, Jonathan Ozik, Mickaël Binois, Kok Ben Toh
Trajectory-Oriented Optimization of Stochastic Epidemiological Models. WSC (2023)
Nicholson T. Collier, Justin M. Wozniak, Abby Stevens, Yadu N. Babuji, Mickaël Binois, Ardindam Fadikar, Alexandra Würth, Kyle Chard, Jonathan Ozik
Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis. CoRR (2023)
Alexandra Würth, Mickaël Binois, Paola Goatin
Validation of Calibration Strategies for Macroscopic Traffic Flow Models on Synthetic Data. MT-ITS (2023)
Nicholson T. Collier, Justin M. Wozniak, Abby Stevens, Yadu N. Babuji, Mickaël Binois, Arindam Fadikar, Alexandra Würth, Kyle Chard, Jonathan Ozik
Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis. IPDPS Workshops (2023)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. Technometrics 64 (4) (2022)
Alexandra Würth, Mickaël Binois, Paola Goatin, Simone Göttlich
Data-driven uncertainty quantification in macroscopic traffic flow models. Adv. Comput. Math. 48 (6) (2022)
Mickaël Binois, Nathan Wycoff
A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization. ACM Trans. Evol. Learn. Optim. 2 (2) (2022)
Stefano Pezzano, Régis Duvigneau, Mickaël Binois
Geometrically consistent aerodynamic optimization using an isogeometric Discontinuous Galerkin method. Comput. Math. Appl. 128 (2022)
Jonathan Ozik, Justin M. Wozniak, Nicholson T. Collier, Charles M. Macal, Mickaël Binois
A population data-driven workflow for COVID-19 modeling and learning. Int. J. High Perform. Comput. Appl. 35 (5) (2021)
Xiong Lyu, Mickaël Binois, Michael Ludkovski
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation. Stat. Comput. 31 (4) (2021)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. CoRR (2021)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. J. Comput. Graph. Stat. 30 (4) (2021)
Mickaël Binois, Robert B. Gramacy
hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. J. Stat. Softw. 98 (1) (2021)
Mickaël Binois, Victor Picheny, Patrick Taillandier, Abderrahmane Habbal
The Kalai-Smorodinsky solution for many-objective Bayesian optimization. J. Mach. Learn. Res. 21 (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)
Matthias Chung, Mickaël Binois, Robert B. Gramacy, Johnathan M. Bardsley, David J. Moquin, Amanda P. Smith, Amber M. Smith
Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. SIAM J. Sci. Comput. 41 (4) (2019)
Mickaël Binois, Jiangeng Huang, Robert B. Gramacy, Mike Ludkovski
Replication or Exploration? Sequential Design for Stochastic Simulation Experiments. Technometrics 61 (1) (2019)
Victor Picheny, Mickaël Binois, Abderrahmane Habbal
A Bayesian optimization approach to find Nash equilibria. J. Glob. Optim. 73 (1) (2019)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. CoRR (2019)
Xiong Lyu, Mickaël Binois, Michael Ludkovski
Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation. CoRR (2018)
Mickaël Binois, David Ginsbourger, Olivier Roustant
A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings. LION (2015)
Mickaël Binois, Didier Rullière, Olivier Roustant
On the estimation of Pareto fronts from the point of view of copula theory. Inf. Sci. 324 (2015)
Mickaël Binois, David Ginsbourger, Olivier Roustant
Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations. Eur. J. Oper. Res. 243 (2) (2015)