most citedRODE-Net: Learning Ordinary Differential Equations with Randomness from Data

4 citations · 4 across the 1 of their papers we have counts for

collaborators

2 papers

math.NA2020★ 4 cited

RODE-Net: Learning Ordinary Differential Equations with Randomness from Data

Junyu Liu, Zichao Long, Ranran Wang +2

Random ordinary differential equations (RODEs), i.e. ODEs with random parameters, are often used to model complex dynamics. Most existing methods to identify unknown governing RODE…

cs.LG2019

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Yufei Wang, Ziju Shen, Zichao Long +1

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solvin…