3 papers
math.NA2026
Learning Chaotic Dynamics through Second-Order Geometric Supervision
Shinhoo Kang, Hai V. Nguyen, Tan Bui-Thanh
Learning chaotic dynamical systems from data requires more than short-term predictive accuracy: the learned model must preserve the attractor geometry and its invariant statistics.…
cs.LG2024
TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems
Hai V. Nguyen, Tan Bui-Thanh, Clint Dawson
Efficient real-time solvers for forward and inverse problems are essential in engineering and science applications. Machine learning surrogate models have emerged as promising alte…
stat.ML2024
A Model-Constrained Discontinuous Galerkin Network (DGNet) for Compressible Euler Equations with Out-of-Distribution Generalization
Hai V. Nguyen, Jau-Uei Chen, Tan Bui-Thanh
Real-time accurate solutions of large-scale complex dynamical systems are critically needed for control, optimization, uncertainty quantification, and decision-making in practical…