Loïc Brevault

According to our database, Loïc Brevault authored at least 15 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables.

Loïc Brevault, Mathieu Balesdent

Eng. Appl. Artif. Intell., 2024

A survey on multi-fidelity surrogates for simulators with functional outputs: unified framework and benchmark.

Lucas Brunel, Mathieu Balesdent, Loïc Brevault, Rodolphe Le Riche, Bruno Sudret

CoRR, 2024

2021

Mixed Variable Gaussian Process-Based Surrogate Modeling Techniques: Application to Aerospace Design.

Julien Pelamatti, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Yannick Guerin

J. Aerosp. Inf. Syst., November, 2021

Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty.

Gabriel Sarazin, Jérôme Morio, Agnès Lagnoux, Mathieu Balesdent, Loïc Brevault

Reliab. Eng. Syst. Saf., 2021

2020

Overview and Comparison of Gaussian Process-Based Surrogate Models for Mixed Continuous and Discrete Variables: Application on Aerospace Design Problems.

Julien Pelamatti, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Yannick Guerin

Proceedings of the High-Performance Simulation-Based Optimization, 2020

Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities.

Loïc Brevault, Mathieu Balesdent, Ali Hebbal

CoRR, 2020

Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes.

Ali Hebbal, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Nouredine Melab

CoRR, 2020

Bayesian optimization of variable-size design space problems.

Julien Pelamatti, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Yannick Guerin

CoRR, 2020

2019

Efficient global optimization of constrained mixed variable problems.

Julien Pelamatti, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Yannick Guerin

J. Glob. Optim., 2019

Bayesian Optimization using Deep Gaussian Processes.

Ali Hebbal, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Nouredine Melab

CoRR, 2019

2018

Efficient Global Optimization using Deep Gaussian Processes.

Ali Hebbal, Loïc Brevault, Mathieu Balesdent, El-Ghazali Talbi, Nouredine Melab

CoRR, 2018

Preliminary study on launch vehicle design: Applications of multidisciplinary design optimization methodologies.

Loïc Brevault, Mathieu Balesdent, Sébastien Defoort

Concurr. Eng. Res. Appl., 2018

Efficient Global Optimization Using Deep Gaussian Processes.

Ali Hebbal, Loïc Brevault, Mathieu Balesdent, Ei-Ghazali Taibi, Nouredine Melab

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2015

Contributions to multidisciplinary design optimization under uncertainty, application to launch vehicle design. (Contributions à l'optimisation multidisciplinaire sous incertitudes, application à la conception de lanceurs).

Loïc Brevault

PhD thesis, 2015

2013

Accident precursors, near misses, and warning signs: Critical review and formal definitions within the framework of Discrete Event Systems.

Joseph Homer Saleh, Elizabeth A. Saltmarsh, Francesca M. Favarò, Loïc Brevault

Reliab. Eng. Syst. Saf., 2013