2 papers
cs.LG2021
Towards a Taxonomy of Graph Learning Datasets
Renming Liu, Semih Cantürk, Frederik Wenkel +10
Graph neural networks (GNNs) have attracted much attention due to their ability to leverage the intrinsic geometries of the underlying data. Although many different types of GNN mo…
cs.LG2021
Molecular Graph Generation via Geometric Scattering
Dhananjay Bhaskar, Jackson D. Grady, Michael A. Perlmutter +1
Graph neural networks (GNNs) have been used extensively for addressing problems in drug design and discovery. Both ligand and target molecules are represented as graphs with node a…