20 citations · 52 across the 6 of their papers we have counts for
4 papers · 1 filter
A Deep Learning Based Discontinuous Galerkin Method for Hyperbolic Equations with Discontinuous Solutions and Random Uncertainties
Jingrun Chen, Shi Jin, Liyao Lyu
We propose a deep learning based discontinuous Galerkin method (D2GM) to solve hyperbolic equations with discontinuous solutions and random uncertainties. The main computational ch…
Enforcing exact boundary and initial conditions in the deep mixed residual method
Liyao Lyu, Keke Wu, Rui Du +1
In theory, boundary and initial conditions are important for the wellposedness of partial differential equations (PDEs). Numerically, these conditions can be enforced exactly in cl…
MIM: A deep mixed residual method for solving high-order partial differential equations
Liyao Lyu, Zhen Zhang, Minxin Chen +1
In recent years, a significant amount of attention has been paid to solve partial differential equations (PDEs) by deep learning. For example, deep Galerkin method (DGM) uses the P…
Quasi-Monte Carlo sampling for machine-learning partial differential equations
Jingrun Chen, Rui Du, Panchi Li +1
Solving partial differential equations in high dimensions by deep neural network has brought significant attentions in recent years. In many scenarios, the loss function is defined…