Publications

Publications

Journal Articles:

• • Pezzano, S., Duvigneau, R. & Binois, M. (2022). Geometrically consistent aerodynamic optimization using an isogeometric Discontinuous Galerkin method. Computers & Mathematics with Applications, 128(15), 368-381. Article Preprint

  • Würth, A., Binois, M., Goatin, P., Göttlich, S. (2022). Data driven uncertainty quantification in macroscopic traffic flow models. Advances in Computational Mathematics, 48(6). Article Preprint

  • Binois, M., Wycoff, N. (2022). A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization. ACM Transactions on Evolutionary Learning and Optimization, 2(2), 1-26. Article Preprint

  • Wycoff, N., Binois, M. & Gramacy, R. (2022). Sensitivity Prewarping for Local Surrogate Modeling. Technometrics, 64(4), 535-547. Article Preprint

  • Elsawy, M., Binois, M., Duvigneau, R., Lanteri, S., Genevet, P. (2021). Optimization of metasurfaces under geometrical uncertainty using statistical learning. Optics Express, 29, 29887-29898. Article

  • Elsawy, M., Gourdin, A., Binois, M., Duvigneau, R., Felbacq, D., Khadir, S., , Genevet, P, Lanteri, S. (2021). Multiobjective statistical learning optimization for large-scale RGB metalens. ACS photonics, 8(8), 2498-2508. Article Preprint 

  • Wycoff, N., Binois, M., Wild, S. (2021). Sequential Learning of Active Subspaces. Journal of Computational and Graphical Statistics, 30(4), 1224-1237. Article  Preprint

  • Ozik, J., Wozniak, J., Collier, N., Macal, C. and Binois, M. (2021). A Population Data-Driven Workflow for COVID-19 Modeling and Learning. International Journal of High Performance Computing Applications, 35(5), 483-499. Article Preprint.

  • Lyu, X., Binois, M. & Ludkovski, M. (2021).  Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation. Statistics and Computing, 31(4). Article Preprint

  • Binois, M., Gramacy, R. B. (2021). hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. Journal of Statistical Software, 98(13). Article  Vignette

  • Binois, M., Picheny, V., Taillandier, P. & Habbal, A. (2020). The Kalai-Smorodinski solution for many-objective Bayesian optimization. Journal of Machine Learning Research 21 (150), 1-42. Article Preprint

  • Huang, J., Gramacy, R. B., Binois, M. & Librashi, M. (2020). On-site surrogates for large-scale calibration. Applied Stochastic Models in Business and Industry, 36, 283-304. Article Preprint

  • Binois, M., Ginsbourger, D. & Roustant, O. (2020). On the choice of the low-dimensional domain for global optimization via random embeddings. Journal of Global Optimization, 76, 69-90. Article Preprint

  • Chung, M., Binois, M., Gramacy, R.B., Moquin, D.J., Smith, A.P. & Smith, A.M. (2019). Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. SIAM Journal on Scientific Computing 41(4), 2212-2238. Article Preprint

  • Picheny, V., Binois, M., & Habbal, A. (2019). A Bayesian optimization approach to find Nash equilibria. Journal of Global Optimization, 73(1), 171-192. Article Preprint

  • Binois, M., Huang, J., Gramacy, R. & Ludkovski, M. (2019).  Replication or exploration? Sequential design for stochastic simulation experiments. Technometrics, 61(1), 7-23 . Article Preprint

  • Binois, M., Gramacy R. & Ludkovski, M. (2018). Practical heteroskedastic Gaussian process modeling for large simulation experiments. Journal of Computational and Graphical Statistics, 27(4), 808-821. Article Preprint

  • Binois, M. & Picheny, V. (2019). GPareto: An R Package for Gaussian-Process Based Multi-Objective Optimization and Analysis. Journal of Statistical Software, 89(8), 1-30. Article Vignette 

  • Binois, M., Ginsbourger,  D., & Roustant, O. (2015). Quantifying uncertainty on Pareto fronts  with Gaussian process conditional simulations. European Journal of Operational Research, 243(2), 386-394. Article Preprint

  • Binois, M., Rulliere, D., & Roustant, O. (2015). On the estimation  of Pareto fronts from the point of view of copula theory. Information Sciences, 324, 270-285. Article Preprint

Conference Proceedings (peer reviewed):

• • Fadikar, A., Binois, M., Collier, N., Stevens, A., Toh, K.,  Ozik, J.. Trajectory-oriented optimization of stochastic epidemiological models. In Winter Simulation Conference 2023. Preprint

  • Musayeva, K.,  Binois, M. (2023). Improved Multi-label Propagation for Small Data with Multi-objective Optimization. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 284 - 300. Article Preprint

  • Würth, A., Binois, M., Goatin, P. (2023). Validation of calibration strategies for macroscopic traffic flow models on synthetic data. In 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), pp. 1-6. Article Preprint

  • Collier N., Wozniak J.M.,  Stevens, A., Babuji, Y., Binois,  M., Fadikar, A., Würth, A., Chard, K., Ozik, J. (2023). Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis. In 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 868-877). Article Preprint

  • Binois, M., Picheny, V. & Habbal, A. (2017). The Kalai-Smorodinski solution for many-objective Bayesian optimization. In BayesOpt workshop at NIPS 2017-31st Conference on Neural Information Processing Systems. Article Preprint

  • Crandell, I., Millican, A., Vasta, R., Smith, E., Alexander, N., Devenport, W., Gramacy, R., & Binois, M. (2017). Anomaly detection in large-scale wind tunnel tests using Gaussian processes. In 33rd AIAA Aerodynamic Measurement Technology and Ground Testing Conference. AIAA AVIATION Forum. Article

  • Binois, M., Ginsbourger,  D., & Roustant, O. (2015). A warped kernel improving robustness in  Bayesian optimization via random embeddings. In Learning and Intelligent Optimization (pp. 281-286). Springer International Publishing. Article Preprint

Book chapters

• Binois, M., Habbal, A., Picheny, P. (2023). A game theoretic perspective on Bayesian multi-objective optimization. Many-Criteria Optimization and Decision Analysis : State-of-the-Art, Present Challenges, and Future Perspectives, pp. 299 - 316. Article  Preprint

Articles in review:

• • Musayeva, K., Binois, M. (2024). Shared active subspace for multivariate vector-valued functions. Preprint

  • Würth, A., Binois, M., Goatin, P. (2023). Traffic prediction by combining macroscopic models and Gaussian processes. Preprint

  • Berti, L., Binois, M., Alouges, F., Aussal, M., Prud'Homme, C. & Giraldi, L. (2021). Shapes enhancing the propulsion of multiflagellated helical microswimmers. Preprint

  • Binois, M., Collier, N., Ozik, J. (2021). A portfolio approach to massively parallel Bayesian optimization. Preprint