Kenneth L. Clarkson, Elad Hazan, et al.
Journal of the ACM
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.
Kenneth L. Clarkson, Elad Hazan, et al.
Journal of the ACM
Yuankai Luo, Veronika Thost, et al.
NeurIPS 2023
Aditya Malik, Nalini Ratha, et al.
CAI 2024
Stephen Obonyo, Isaiah Onando Mulang’, et al.
NeurIPS 2023