Gosia Lazuka, Andreea Simona Anghel, et al.
SC 2024
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.
Gosia Lazuka, Andreea Simona Anghel, et al.
SC 2024
Natalia Martinez Gil, Kanthi Sarpatwar, et al.
NeurIPS 2023
Robert Farrell, Rajarshi Das, et al.
AAAI-SS 2010
Fan Feng, Sara Magliacane
NeurIPS 2023