2 papers
physics.flu-dyn2026
Split Complex-Valued Physics-Informed Neural Networks for Forward and Inverse Nonlinear PDEs
Biswanath Barman, Rajendra K. Ray, Debdeep Chatterjee
Physics-informed neural networks (PINNs) have emerged as a powerful framework for solving forward and inverse partial differential equations (PDEs), but conventional real-valued PI…
physics.flu-dyn2026
A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations
Biswanath Barman, Debdeep Chatterjee, Rajendra K. Ray
Traditional computational fluid dynamics and physics-informed neural networks (PINNs) often suffer from high computational cost, mesh sensitivity, and reduced accuracy for strongly…