Open sgbaird opened 2 years ago
Hey, thanks for the question. As mentioned in the "baseline models" section of the paper, we extended CrabNet to multi-property prediction by changing the last layers of the DNNs to produce the desired output dimension. This should be easy to implement upon CrabNet's codes.
@sk2299, thanks for the quick reply! As I was digging a bit deeper, I found the relevant place in CrabNet
, and while the change looks simple, it might be a bit involved to actually get it working. Do you still have a copy of your implementation? It would be nice to have a working example to compare/debug against. Also, what about for CrabNetMP(T)
(transfer learning)? From the paper, I see:
Specifically, we concatenated each generated DOS vector to the respective latent vector from the model’s encoder, creating a latent representation with MPDOS transfer learning that served as the input to the model’s decoder.
Do you have a copy of your implementation for this one, too?
@sk2299, a search for "CrabNet" within the repository returns no results.