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arXiv · 2309.16374

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

Akihiro Kishimoto·Hiroshi Kajino·Masataka Hirose·Junta Fuchiwaki·Indra Priyadarsini·Lisa Hamada·Hajime Shinohara·Daiju Nakano·Seiji Takeda
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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.

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Akihiro Kishimoto, Hiroshi Kajino, Masataka Hirose, Junta Fuchiwaki, Indra Priyadarsini, Lisa Hamada, Hajime Shinohara, Daiju Nakano, Seiji Takeda. 2023-09-28. MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network. https://arxiv.org/abs/2309.16374

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