Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach

24 May 2019

Papers citing "Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach"

8 / 8 papers shown

Title
Node Centrality Approximation For Large Networks Based On Inductive Graph Neural Networks Yiwei Zou Ting Li Zong-fu Luo GNN 37 0 0 08 Mar 2024
Edge Ranking of Graphs in Transportation Networks using a Graph Neural Network (GNN) D. Jana Sven Malama S. Narasimhan E. Taciroğlu GNN 26 3 0 25 Mar 2023
Can one hear the position of nodes? Rami Puzis 23 2 0 10 Nov 2022
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm Wentao Zhang Yu Shen Zheyu Lin Yang Li Xiaosen Li Wenbin Ouyang Yangyu Tao Zhi-Xin Yang Bin Cui GNN 29 59 0 01 Mar 2022
Stable Prediction on Graphs with Agnostic Distribution Shift Shengyu Zhang Kun Kuang J. Qiu Jin Yu Zhou Zhao Hongxia Yang Zhongfei Zhang Fei Wu OOD 39 8 0 08 Oct 2021
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks Cunchao Zhu Muhao Chen Changjun Fan Guangquan Cheng Yan Zhan 13 247 0 15 Dec 2020
Neural Subgraph Isomorphism Counting Xin Liu Haojie Pan Mutian He Yangqiu Song Xin Jiang Lifeng Shang GNN 22 78 0 25 Dec 2019
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,945 0 09 Jun 2018