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Uncertainty Driven Active Learning of Coarse Grained Free Energy Models
And I'm very interested in the CGMD simulation results of the article. I'm really interested in learning about the implementation in the paper and probably using it in the future. Obviously, unlike DFT-MD, the key to success for CGMD is the reverse mapping for active learning, which does not seem to exist in the current version.
Is the specific coarse-grain version available? It would be helpful if the CG version is included!
The text was updated successfully, but these errors were encountered:
Hi there! We're working on cleaning up the CG code, documenting it, etc. with some more recent features, so it is currently private. We're hoping to make it public ASAP. However, please feel free to email me (email should be in the preprint) and I'd be happy to discuss your needs and timelines, etc. and share some code earlier than release if I can.
Hi,
Thanks for developing and sharing the code!
I have read the paper
And I'm very interested in the CGMD simulation results of the article. I'm really interested in learning about the implementation in the paper and probably using it in the future. Obviously, unlike DFT-MD, the key to success for CGMD is the reverse mapping for active learning, which does not seem to exist in the current version.
Is the specific coarse-grain version available? It would be helpful if the CG version is included!
The text was updated successfully, but these errors were encountered: