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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?
The text was updated successfully, but these errors were encountered:
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?
The text was updated successfully, but these errors were encountered: