A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings. - Mickaël Binois; David Ginsbourger; Olivier Roustant (LION, 2015)

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations. - Mickaël Binois; David Ginsbourger; Olivier Roustant (Eur. J. Oper. Res., 2015)

On the estimation of Pareto fronts from the point of view of copula theory. - Mickaël Binois; Didier Rullière; Olivier Roustant (Inf. Sci., 2015)

A Bayesian optimization approach to find Nash equilibria. - Victor Picheny; Mickaël Binois; Abderrahmane Habbal (J. Glob. Optim., 2019)

Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. - Matthias Chung; Mickaël Binois; Robert B. Gramacy; Johnathan M. Bardsley; David J. Moquin; Amanda P. Smith; Amber M. Smith (SIAM J. Sci. Comput., 2019)

Replication or Exploration? Sequential Design for Stochastic Simulation Experiments. - Mickaël Binois; Jiangeng Huang; Robert B. Gramacy; Mike Ludkovski (Technometrics, 2019)

On the choice of the low-dimensional domain for global optimization via random embeddings. - Mickaël Binois; David Ginsbourger; Olivier Roustant (J. Glob. Optim., 2020)

The Kalai-Smorodinsky solution for many-objective Bayesian optimization. - Mickaël Binois; Victor Picheny; Patrick Taillandier; Abderrahmane Habbal (J. Mach. Learn. Res., 2020)

A population data-driven workflow for COVID-19 modeling and learning. - Jonathan Ozik; Justin M. Wozniak; Nicholson T. Collier; Charles M. Macal; Mickaël Binois (Int. J. High Perform. Comput. Appl., 2021)

Sequential Learning of Active Subspaces. - Nathan Wycoff; Mickaël Binois; Stefan M. Wild (J. Comput. Graph. Stat., 2021)

hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. - Mickaël Binois; Robert B. Gramacy (J. Stat. Softw., 2021)

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation. - Xiong Lyu; Mickaël Binois; Michael Ludkovski (Stat. Comput., 2021)

Data-driven uncertainty quantification in macroscopic traffic flow models. - Alexandra Würth; Mickaël Binois; Paola Goatin; Simone Göttlich (Adv. Comput. Math., 2022)

Geometrically consistent aerodynamic optimization using an isogeometric Discontinuous Galerkin method. - Stefano Pezzano; Régis Duvigneau; Mickaël Binois (Comput. Math. Appl., 2022)

Sensitivity Prewarping for Local Surrogate Modeling. - Nathan Wycoff; Mickaël Binois; Robert B. Gramacy (Technometrics, 2022)

A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization. - Mickaël Binois; Nathan Wycoff (ACM Trans. Evol. Learn. Optim., 2022)

Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis. - Nicholson T. Collier; Justin M. Wozniak; Abby Stevens; Yadu N. Babuji; Mickaël Binois; Arindam Fadikar; Alexandra Würth; Kyle Chard; Jonathan Ozik (IPDPS Workshops, 2023)

Validation of Calibration Strategies for Macroscopic Traffic Flow Models on Synthetic Data. - Alexandra Würth; Mickaël Binois; Paola Goatin (MT-ITS, 2023)

Improved Multi-label Propagation for Small Data with Multi-objective Optimization. - Khadija Musayeva; Mickaël Binois (ECML/PKDD (4), 2023)

Trajectory-Oriented Optimization of Stochastic Epidemiological Models. - Arindam Fadikar; Nicholson T. Collier; Abby Stevens; Jonathan Ozik; Mickaël Binois; Kok Ben Toh (WSC, 2023)

A Game Theoretic Perspective on Bayesian Many-Objective Optimization. - Mickaël Binois; Abderrahmane Habbal; Victor Picheny (Many-Criteria Optimization and Decision Analysis, 2023)

Decoupled Design of Experiments for Expensive Multi-objective Problems. - Mickaël Binois; Jürgen Branke; Jonathan E. Fieldsend; Robin C. Purshouse (LION, 2024)

Shared active subspace for multivariate vector-valued functions. - Khadija Musayeva; Mickaël Binois (CoRR, 2024)

A Portfolio Approach to Massively Parallel Bayesian Optimization. - Mickaël Binois; Nicholson T. Collier; Jonathan Ozik (J. Artif. Intell. Res., 2025)

hetGPy: Heteroskedastic Gaussian Process Modeling in Python. - David O'Gara; Mickaël Binois; Roman Garnett; Ross A. Hammond (J. Open Source Softw., 2025)

Modular Jump Gaussian Processes. - Anna R. Flowers; Christopher T. Franck; Mickaël Binois; Chiwoo Park; Robert B. Gramacy (CoRR, 2025)