Hierarchical Inter-Message Passing for Learning on Molecular Graphs

22 June 2020

Papers citing "Hierarchical Inter-Message Passing for Learning on Molecular Graphs"

7 / 57 papers shown

Title
Graph convolutions that can finally model local structure Rémy Brossard Oriel Frigo David Dehaene GNN 34 48 0 30 Nov 2020
Improving Graph Property Prediction with Generalized Readout Functions Eric Alcaide OOD AI4CE 16 0 0 21 Sep 2020
Building powerful and equivariant graph neural networks with structural message-passing Clément Vignac Andreas Loukas P. Frossard 31 119 0 26 Jun 2020
Wasserstein Embedding for Graph Learning Soheil Kolouri Navid Naderializadeh Gustavo K. Rohde Heiko Hoffmann GNN 24 85 0 16 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 55 424 0 16 Jun 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 181 1,778 0 02 Mar 2017