kenko911
commented
10 months ago Hi, sorry for the late reply. here is the link https://doi.org/10.5281/zenodo.4072029 for reproducing band gap in the the paper. We will upload the multi-fidelity MEGNet band gap example for the MatGL version soon. It should be noted that the set2set layer implementation is different from the Tensorflow version and therefore the results would be different but qualitatively the same. Please stay tune!
Email (Optional)
airevolt1973@yahoo.com
Problem
I am trying to reproduce the results in
Chen, C.; Zuo, Y.; Ye, W.; Li, X.; Ong, S. P. Learning Properties of Ordered and Disordered Materials from Multi-Fidelity Data. Nature Computational Science, 2021, 1, 46–53.
for the extended QM7b energy data set (Extended data Fig 4b of the paper).
Following the instructions and looking at the code for the band gap example in the paper, the code for which is provided in GitHub, I set the 'state' variable/key in the structures to either 1 for low fidelity or 2 for high fidelity. This information is then passed as global feature setting nfeat_global = 1, global_embedding_dim=None.
However, I cannot reproduce the results using the default megnet with 3 blocks, 3 message passing step and graph_converter=CrystalGraph with the Gaussian distance method. Very little information was provided in the paper on this example and there is no information on the Github page.
Could you please upload the code for that example or else let me know the precise details how to implement the multi-fidelity version for that example please? Much appreciated.
Proposed Solution
if possible, could you upload the code for generating the results of Fig 4b?
Alternatives
No response
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