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Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules.
Jong Youl Choi
Pei Zhang
Kshitij Mehta
Andrew Blanchard
Massimiliano Lupo Pasini
Published in:
J. Cheminformatics (2022)
Keyphrases
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convolutional neural networks
convolutional network
training set
random walk
test set
graph theory
structured data
training process
directed graph
graph structure
training data
supervised learning
training examples
graph mining
molecular interactions