FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning

1. 1Build a graph-to-sequence model using FragmentNet
2. 2Run adaptive graph fragmentation on molecular graphs
3. 3Configure the model to decompose molecules into chemically valid fragments
4. 4Test the model's ability to capture meaningful chemical substructure context
5. 5Apply FragmentNet to various molecular representation learning tasks

Data scientists and AI engineers working on molecular representation learning tasks can benefit from FragmentNet to improve model performance and chemists can utilize the results for better understanding of molecular structures

💡 Adaptive graph fragmentation can improve capture of chemical substructure context in molecular representation learning

💡 FragmentNet: Adaptive graph fragmentation for molecular representation learning