What is a physics informed neural network?

A Physics Informed Neural Network (PINN) is a type of machine learning model that incorporates physical laws, typically expressed as partial differential equations, into the training process of neural networks. By embedding these physical constraints, PINNs can solve forward and inverse problems in engineering and science more accurately and efficiently, even with limited data. They are especially useful for modeling complex systems where traditional data-driven approaches might fail to generalize or respect fundamental physical principles.