줌: https://snu-ac-kr.zoom.us/j/4020312420

The Neural network-based approach to solving partial differential equations has attracted considerable attention due to its simplicity and flexibility to represent the solution of the partial differential equation. In particular, data-driven methods have been developed to learn dynamical systems and partial differential equations (PDE). In this talk, we propose a novel Legendre-Galerkin Deep Neural Network (LGNet) algorithm to predict solutions to various differential equations