PEROVSKITE SYNTHESIZABILITY PREDICTION METHOD USING GRAPH CONVOLUTIONAL NEURAL NETWORKS AND POSITIVE UNLABELED LEARNING
Abstract:
Provided is a method for predicting perovskite synthesizability using a graph convolutional neural network and positive unlabeled learning, capable of predicting perovskite synthesizability by using a graph convolutional neutral network and positive unlabeled learning which is semi-supervised learning based on a labeled model using positive data and positive unlabeled data.
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