Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization

13 June 2019

Papers citing "Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization"

7 / 7 papers shown

Title
Neural combinatorial optimization beyond the TSP: Existing architectures under-represent graph structure Matteo Boffa Zied Ben-Houidi J. Krolikowski Dario Rossi GNN 20 7 0 03 Jan 2022
GNN-Geo: A Graph Neural Network-based Fine-grained IP geolocation Framework Shichang Ding Xiangyang Luo Jinwei Wang Xiaoming Fu 19 14 0 18 Dec 2021
Systematic Generalization with Edge Transformers Leon Bergen Timothy J. O'Donnell Dzmitry Bahdanau 10 46 0 01 Dec 2021
3D Infomax improves GNNs for Molecular Property Prediction Hannes Stärk Dominique Beaini Gabriele Corso Prudencio Tossou Christian Dallago Stephan Günnemann Pietro Lió AI4CE 25 203 0 08 Oct 2021
Large-Scale Chemical Language Representations Capture Molecular Structure and Properties Jerret Ross Brian M. Belgodere Vijil Chenthamarakshan Inkit Padhi Youssef Mroueh Payel Das AI4CE 19 272 0 17 Jun 2021
Self-supervised edge features for improved Graph Neural Network training Arijit Sehanobish N. Ravindra David van Dijk SSL 10 6 0 23 Jun 2020
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 33 840 0 31 Jul 2019