Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.
MIT License
141
stars
46
forks
source link
Adding an API documentation for new forks of the PINN approach #3
[x] add setter for HPM module in PINN interface (setHPMnetwork)
[x] add branching in pde loss in PINN interface => go either into analytical PDE loss or HPM PDE loss
[ ] rename "initial_loss" into "interpolation_loss"
[ ] add train method to PINN interface
[ ] add interface for models within PINN interface => e.g. one/two method should provide additional loss terms (if necessary) for interpolation and PDE learning