MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network

MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network

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 vari...

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Hauptverfasser: Kishimoto, Akihiro, Kajino, Hiroshi, Hirose, Masataka, Fuchiwaki, Junta, Priyadarsini, Indra, Hamada, Lisa, Shinohara, Hajime, Nakano, Daiju, Takeda, Seiji
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Sprache:eng
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Computer Science - Learning
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Zusammenfassung: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.
DOI:10.48550/arxiv.2309.16374