Dear community,
Data-driven and physics-informed versions of deeponet may be used in different fields with their unique merits.
In my reseach, I have some data as well as some physics (PDE), so I want to use them simultaneously in deeponet. Herein, my data is randonly distributed in 3D space not at the boundary of the problem domain.
So have can I feed these data for deeponet, while use the pde as well?
Dear community, Data-driven and physics-informed versions of deeponet may be used in different fields with their unique merits. In my reseach, I have some data as well as some physics (PDE), so I want to use them simultaneously in deeponet. Herein, my data is randonly distributed in 3D space not at the boundary of the problem domain. So have can I feed these data for deeponet, while use the pde as well?