most citedBayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design

9 citations · 18 across the 6 of their papers we have counts for

collaborators

9 papers

cs.AI20251 cited

Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration

Paul Saves, Pramudita Satria Palar, Muhammad Daffa Robani +6

Complex systems are increasingly explored through simulation-driven engineering workflows that combine physics-based and empirical models with optimization and analytics. Despite t…

cs.CE20255 cited

Efficient Multi-Objective Constrained Bayesian Optimization of Bridge Girder

Heine Havneraas Røstum, Joseph Morlier, Sebastien Gros +1

The buildings and construction sector is a significant source of greenhouse gas emissions, with cement production alone contributing 7~\% of global emissions and the industry as a…

cs.LG2025

Frequency-aware Surrogate Modeling With SMT Kernels For Advanced Data Forecasting

Nicolas Gonel, Paul Saves, Joseph Morlier

This paper introduces a comprehensive open-source framework for developing correlation kernels, with a particular focus on user-defined and composition of kernels for surrogate mod…

cs.LG2025

NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis

Mouadh Yagoubi, David Danan, Milad Leyli-Abadi +15

The integration of machine learning (ML) into the physical sciences is reshaping computational paradigms, offering the potential to accelerate demanding simulations such as computa…

physics.flu-dyn2025

Towards scalable surrogate models based on Neural Fields for large scale aerodynamic simulations

Giovanni Catalani, Jean Fesquet, Xavier Bertrand +3

This paper introduces a novel surrogate modeling framework for aerodynamic applications based on Neural Fields. The proposed approach, MARIO (Modulated Aerodynamic Resolution Invar…

cs.LG20253 cited

Multi-objective Bayesian Optimization With Mixed-categorical Design Variables for Expensive-to-evaluate Aeronautical Applications

Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage +8

This work aims at developing new methodologies to optimize computational costly complex systems (e.g., aeronautical engineering systems). The proposed surrogate-based method (often…