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

Understand

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 RODEs from observed data often rely on strong prior knowledge.
• Extracting the governing equations from data with less prior knowledge remains a great challenge.