4 papers
Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners
Juntao Wang, Jiwei Jia, Xinliang Liu
High-frequency Helmholtz problems in heterogeneous media remain challenging for both classical iterative methods and end-to-end neural PDE solvers. We propose Neural Preconditioned…
A Filtered MgNet Solver For Radiative Transfer Equations
Qinchen Song, Xinliang Liu, Lei Zhang
Conventional numerical solvers for the radiative transfer equation (RTE) exhibit severe sensitivity to medium parameters. To address this, we propose an operator learning framework…
Divergence-free Linearized Neural Networks: Integral Representation and Optimal Approximation Rates
Juncai He, Xinliang Liu, Zitong Tian
This paper studies the numerical approximation of divergence-free vector fields by linearized shallow neural networks, also referred to as random feature models or finite neuron sp…
Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations
Wenrui Hao, Xinliang Liu, Yahong Yang
Solving nonlinear partial differential equations (PDEs) with multiple solutions using neural networks has found widespread applications in various fields such as physics, biology,…