7 citations · 7 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2026
Hard Constraint Projection in a Physics Informed Neural Network
Miranda J. S. Horne, Peter K. Jimack, Amirul Khan +1
In this work, we embed hard constraints in a physics informed neural network (PINN) which predicts solutions to the 2D incompressible Navier Stokes equations. We extend the hard co…
cs.LG2024★ 7 cited
Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs
Jose Florido, He Wang, Amirul Khan +1
Physics-informed neural networks (PINNs) provide a means of obtaining approximate solutions of partial differential equations and systems through the minimisation of an objective f…