Author

Bangti Jin

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Preprint Aug 2026

On the extreme eigenvalues of the Gram Matrix in Physics-Informed Neural Networks for the Poisson Equation

The smallest and largest eigenvalues of the Gram matrix induced by the differential neural tangent kernel (DNTK) play a pivotal role in the analysis of over-parameterized PINNs trained by gradient type algorithms. However, a theoretical analysis of the extreme eigenvalues remains completely absent due to the challenge...

Bang-Ti Jin, Longjun Wu · 0 citations

#machine learning Preprint Sep 2026

A Hybrid Iterative Deep Ritz Method for Elliptic Interface Problems

Numerical experiments indicate that the H-IDRM outperforms existing neural solvers on problems with high-dimensional domains, intricate interface geometries, and lower subdomain regularity.

Tian-Hao Hu, Bang-Ti Jin, Feng-Ru Wang et al. · 0 citations

Preprint Jul 2026

The Differential Neural Tangent Kernel and Its Positivity

The Neural Tangent Kernel (NTK) is one powerful tool for analyzing the training dynamics of neural networks in the over-parameterized regime. Recently, the theoretical framework has been extended to physics-informed neural networks (PINNs) for solving linear PDEs, one highly popular class of neural PDE solvers. In the...

Bangti Jin, Longjun Wu · 1 citation · ⚡1