activity
20222025
most citedCD-ROM: Complemented Deep-Reduced Order Model

15 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 1 cited

PLAID: A Unified Data Model for Machine Learning on Heterogeneous Physics Simulations

Fabien Casenave, Xavier Roynard, Brian Staber +17

Machine learning-based surrogate models have emerged as a powerful tool to accelerate simulation-driven scientific workflows, but their adoption is limited by the lack of large-sca…

stat.ML2023★ 3 cited

Interpretable learning of effective dynamics for multiscale systems

Emmanuel Menier, Sebastian Kaltenbach, Mouadh Yagoubi +2

The modeling and simulation of high-dimensional multiscale systems is a critical challenge across all areas of science and engineering. It is broadly believed that even with today'…

cs.LG2022

Continuous Methods : Adaptively intrusive reduced order model closure

Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi +4

Reduced order modeling methods are often used as a mean to reduce simulation costs in industrial applications. Despite their computational advantages, reduced order models (ROMs) o…

cs.CV2022★ 1 cited

Continuous Methods : Hamiltonian Domain Translation

Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi +2

This paper proposes a novel approach to domain translation. Leveraging established parallels between generative models and dynamical systems, we propose a reformulation of the Cycl…

physics.flu-dyn2022★ 15 cited

CD-ROM: Complemented Deep-Reduced Order Model

Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi +2

Model order reduction through the POD-Galerkin method can lead to dramatic gains in terms of computational efficiency in solving physical problems. However, the applicability of th…