DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation

Understand

We present a method for learning dynamics of complex physical processes described by time-dependent nonlinear partial differential equations (PDEs).

• Our particular interest lies in extrapolating solutions in time beyond the range of temporal domain used in training.
• Our choice for a baseline method is physics-informed neural network (PINN) [Raissi et al., J.
• Comput.