Closed LanceKnight closed 2 years ago
Hi @LanceKnight,
Thanks for your suggestion. We exactly followed the SchNet paper and fixed the output dimension as 1. I updated our code here so that users can define the output dimension.
Thanks, Limei
Thank you! @limei0307
Hello, it seems the output of SchNet is of dimension 1, which is the prediction dimension. Is it possible to change to output the graph embedding instead of the predicton? This way it's more flexible for the users to put whatever downstream classifier after the embedding and have a control of how many prediction dimension there can be (multi-task potentially)