scientific computing

Physics-informed neural networks (PINNs) are a class of deep learning models that incorporate physical laws, typically expressed as differential equations, into the training process. By embedding these constraints, PINNs can solve forward and inverse problems in scientific computing with improved accuracy and generalization.