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Reproducing GraphRNN
The easiest path in is likely some applied workshop/conference.
A good narrative would be to:
Alternatively, we could find a metric (rather than a domain) where GraphRNN performs poorly.
The scheduler in the original codebase is called every batch: this means that the milestones are effectively 32x smaller.
https://github.com/JiaxuanYou/graph-generation/blob/master/train.py#L218
Maybe use algebraic topology stuff @skandermoalla
Hey,
Thanks so much for the new implmentation of GraphRNN! I have run the example script successfully. I am working on generation of crystal based on the graph representation. For crystal, global features for unit cell and edge features for bonds are needed. Can this model generate such features of graph? If so, how to use it? If not, how can I modify the code to implement it?
Thanks!
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