4 papers
Physics Informed Random Feature Neural Networks for Solving PDEs
Chi-An Chen, Chunyang Liao, Ming Zhong
Machine learning-based partial differential equations (PDEs) solvers have attracted significant attention in recent years. Most progress in this area has been driven by deep neural…
Unified Learning of the Profile Function in Discrete Keller-Segel Models
Chi-An Chen, Chun Liu, Ming Zhong
We propose a unified learning framework for identifying the profile function in discrete Keller-Segel equations, which are widely used mathematical models for understanding chemota…
On a Modified Random Genetic Drift Model: Derivation and a Structure-Preserving Operator-Splitting Discretization
Chi-An Chen, Chun Liu, Yiwei Wang
One of the fundamental mathematical models for studying random genetic drift is the Kimura equation, derived as the large-population limit of the discrete Wright-Fisher model. Howe…
Finite Difference Approximation with ADI Scheme for Two-dimensional Keller-Segel Equations
Yubin Lu, Chi-An Chen, Xiaofan Li +1
Keller-Segel systems are a set of nonlinear partial differential equations used to model chemotaxis in biology. In this paper, we propose two alternating direction implicit (ADI) s…