Physics informed neural networks is huge area of research in applied engineering, quantum chemistry and physics.

Three major schools of approach are

1. Function approximation - originating from lagaris et al
2. Operator learning - karniadikis (deepOnets) and Caltech ( Fourier neural operator l) FNO is getting more adverts due to Nvidia trying to make it 'the' model
3. Graph neural network approach - Battaglia et al .. this is primarily used for studying problems framed as large scale interactive systems of X where X is particles , objects

We do active work in this space