8 citations · 8 across the 3 of their papers we have counts for
4 papers
WGFINNs: Weak formulation-based GENERIC formalism informed neural networks
Jun Sur Richard Park, Auroni Huque Hashim, Siu Wun Cheung +2
Data-driven discovery of governing equations from noisy observations remains a fundamental challenge in scientific machine learning. While GENERIC formalism informed neural network…
Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems
Xiaolong He, Yeonjong Shin, Anthony Gruber +3
We propose an efficient thermodynamics-informed latent space dynamics identification (tLaSDI) framework for the reduced-order modeling of parametric nonlinear dynamical systems. Th…
tLaSDI: Thermodynamics-informed latent space dynamics identification
Jun Sur Richard Park, Siu Wun Cheung, Youngsoo Choi +1
We propose a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an…
A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling
Christophe Bonneville, Xiaolong He, April Tran +10
Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in…