21 citations · 23 across the 4 of their papers we have counts for
4 papers
Hyper-reduction methods for accelerating nonlinear finite element simulations: open source implementation and reproducible benchmarks
Axel Larsson, Minji Kim, Chris Vales +4
Hyper-reduction methods have gained increasing attention for their potential to accelerate reduced order models for nonlinear systems, yet their comparative accuracy and computatio…
Machine-precision energy conservative reduced models for Lagrangian hydrodynamics by quadrature methods
Chris Vales, Siu Wun Cheung, Dylan M. Copeland +1
We present an energy conservative, quadrature based model reduction framework for the compressible Euler equations of Lagrangian hydrodynamics. Building on a finite element discret…
Defining Foundation Models for Computational Science: A Call for Clarity and Rigor
Youngsoo Choi, Siu Wun Cheung, Youngkyu Kim +9
The widespread success of foundation models in natural language processing and computer vision has inspired researchers to extend the concept to scientific machine learning and com…
High-performance finite elements with MFEM
Julian Andrej, Nabil Atallah, Jan-Phillip Bäcker +15
The MFEM (Modular Finite Element Methods) library is a high-performance C++ library for finite element discretizations. MFEM supports numerous types of finite element methods and i…