29 citations · 32 across the 4 of their papers we have counts for
5 papers
Hybrid coupling with numerics-informed neural networks and the overlapping Schwarz alternating method
George Chumbipuma, Irina Tezaur, Alejandro Diaz +1
We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using the overlapping Schwarz alte…
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…
Scalable nonlinear manifold reduced order model for dynamical systems
Ivan Zanardi, Alejandro N. Diaz, Seung Whan Chung +2
The domain decomposition (DD) nonlinear-manifold reduced-order model (NM-ROM) represents a computationally efficient method for integrating underlying physics principles into a neu…
Nonlinear-manifold reduced order models with domain decomposition
Alejandro N. Diaz, Youngsoo Choi, Matthias Heinkenschloss
A nonlinear-manifold reduced order model (NM-ROM) is a great way of incorporating underlying physics principles into a neural network-based data-driven approach. We combine NM-ROMs…
A fast and accurate domain-decomposition nonlinear manifold reduced order model
Alejandro N. Diaz, Youngsoo Choi, Matthias Heinkenschloss
This paper integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM-ROMs approximate the full order model (FOM) state in a nonlinear-manifold…