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
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…