Pranjal Prasad

Locally adaptive Physics-Informed Neural Networks for nonlinear partial differential equations

Physics-Informed Neural Networks (PINNs) have emerged as a powerful paradigm for solving forward and inverse problems governed by partial differential equations (PDEs). However, standard PINNs often struggle with convergence and accuracy, especially when solving non-linear PDEs....