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Publication
NeurIPS 2023
Workshop paper
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network
Abstract
Property prediction plays an important role in material discovery. As an initial step to eventually develop a foundation model for material science, we introduce a new autoencoder called the MHG-GNN, which combines graph neural network (GNN) with Molecular Hypergraph Grammar (MHG). Results on a variety of property prediction tasks with diverse materials show that MHG-GNN is promising.