447 citations · 524 across the 6 of their papers we have counts for
6 papers
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations
Yaohua Zang, Gang Bao
Deep neural networks (DNNs) have been widely used to solve partial differential equations (PDEs) in recent years. In this work, a novel deep learning-based framework named Particle…
Solving Optimal Control Problems of Rigid-Body Dynamics with Collisions Using the Hybrid Minimum Principle
Wei Hu, Jihao Long, Yaohua Zang +2
Collisions are common in many dynamical systems with real applications. They can be formulated as hybrid dynamical systems with discontinuities automatically triggered when states…
A Machine Learning Enhanced Algorithm for the Optimal Landing Problem
Yaohua Zang, Jihao Long, Xuanxi Zhang +3
We propose a machine learning enhanced algorithm for solving the optimal landing problem. Using Pontryagin's minimum principle, we derive a two-point boundary value problem for the…
Numerical Solution of Inverse Problems by Weak Adversarial Networks
Gang Bao, Xiaojing Ye, Yaohua Zang +1
We consider a weak adversarial network approach to numerically solve a class of inverse problems, including electrical impedance tomography and dynamic electrical impedance tomogra…
Weak Adversarial Networks for High-dimensional Partial Differential Equations
Yaohua Zang, Gang Bao, Xiaojing Ye +1
Solving general high-dimensional partial differential equations (PDE) is a long-standing challenge in numerical mathematics. In this paper, we propose a novel approach to solve hig…
A Jump Stochastic Differential Equation Approach for Influence Prediction on Information Propagation Networks
Yaohua Zang, Gang Bao, Xiaojing Ye +2
We propose a novel problem formulation of continuous-time information propagation on heterogenous networks based on jump stochastic differential equations (SDE). The structure of t…