59 citations · 82 across the 8 of their papers we have counts for
3 papers · 1 filter
Physics-Informed Machine Learning for Two-Phase Moving-Interface and Stefan Problems
Che-Chia Chang, Te-Sheng Lin, Ming-Chih Lai
The Stefan problem is a classical free-boundary problem that models phase-change processes and poses computational challenges due to its moving interface and nonlinear temperature-…
A categorical embedding discontinuity-capturing shallow neural network for anisotropic elliptic interface problems
Wei-Fan Hu, Te-Sheng Lin, Yu-Hau Tseng +1
In this paper, we propose a categorical embedding discontinuity-capturing shallow neural network for anisotropic elliptic interface problems. The architecture comprises three hidde…
Consistency Training with Physical Constraints
Che-Chia Chang, Chen-Yang Dai, Te-Sheng Lin +2
We propose a physics-aware Consistency Training (CT) method that accelerates sampling in Diffusion Models with physical constraints. Our approach leverages a two-stage strategy: (1…