Learning the Delay Using Neural Delay Differential Equations

Understand

The intersection of machine learning and dynamical systems has generated considerable interest recently.

• Neural Ordinary Differential Equations (NODEs) represent a rich overlap between these fields.
• In this paper, we develop a continuous time neural network approach based on Delay Differential Equations (DDEs).
• Our model uses the adjoint sensitivity method to learn the model parameters and delay directly from data.