complex-valued neural networks 1forward and inverse problems 1oscillatory dynamics 1partial differential equations 1physics-informed neural networks 1
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physics.flu-dyn2026
Split Complex-Valued Physics-Informed Neural Networks for Forward and Inverse Nonlinear PDEs
Biswanath Barman, Rajendra K. Ray, Debdeep Chatterjee
The paper introduces split complex-valued physics-informed neural networks (SCV-PINNs) that use complex-valued parameters and split activations to better capture amplitude and phas…
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…