27 citations · 65 across the 6 of their papers we have counts for
6 papers
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…
Pruning deep neural networks generates a sparse, bio-inspired nonlinear controller for insect flight
Olivia Zahn, Jorge Bustamante, Callin Switzer +2
Insect flight is a strongly nonlinear and actuated dynamical system. As such, strategies for understanding its control have typically relied on either model-based methods or linear…
Optimal piecewise linear data compression for solutions of parametrized partial differential equations
Thomas Daniel, Fabien Casenave, Nissrine Akkari +1
Model order reduction has been extensively studied over the last two decades. Projection-based methods such as the Proper Orthogonal Decomposition and the Reduced Basis Method enjo…
Uncertainty quantification for industrial design using dictionaries of reduced order models
Thomas Daniel, Fabien Casenave, Nissrine Akkari +2
We consider the dictionary-based ROM-net (Reduced Order Model) framework [T. Daniel, F. Casenave, N. Akkari, D. Ryckelynck, Model order reduction assisted by deep neural networks (…
Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases
Thomas Daniel, Fabien Casenave, Nissrine Akkari +2
Nonlinear model order reduction has opened the door to parameter optimization and uncertainty quantification in complex physics problems governed by nonlinear equations. In particu…
Data augmentation and feature selection for automatic model recommendation in computational physics
Thomas Daniel, Fabien Casenave, Nissrine Akkari +1
Classification algorithms have recently found applications in computational physics for the selection of numerical methods or models adapted to the environment and the state of the…