Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1906.12330
Cited By
Graph Star Net for Generalized Multi-Task Learning
21 June 2019
H. Lu
Seth H. Huang
Tian Ye
Xiuyan Guo
GNN
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Graph Star Net for Generalized Multi-Task Learning"
12 / 12 papers shown
Title
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classification
Yan Pang
Chao Liu
GNN
24
8
0
04 Jan 2022
Measuring and Sampling: A Metric-guided Subgraph Learning Framework for Graph Neural Network
Jiyang Bai
Yuxiang Ren
Jiawei Zhang
33
3
0
30 Dec 2021
Structure-Aware Label Smoothing for Graph Neural Networks
Yiwei Wang
Yujun Cai
Yuxuan Liang
Wei Wang
Henghui Ding
Muhao Chen
Jing Tang
Bryan Hooi
31
3
0
01 Dec 2021
KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs
Yinquan Lu
H. Lu
Guirong Fu
Qun Liu
KELM
18
34
0
09 Sep 2021
Scalable Graph Neural Networks via Bidirectional Propagation
Ming Chen
Zhewei Wei
Bolin Ding
Yaliang Li
Ye Yuan
Xiaoyong Du
Ji-Rong Wen
GNN
18
142
0
29 Oct 2020
NENET: An Edge Learnable Network for Link Prediction in Scene Text
M. Singh
Sayan Banerjee
S. Chaudhuri
21
1
0
25 May 2020
Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network
Jiyang Bai
Yuxiang Ren
Jiawei Zhang
GNN
19
29
0
17 Feb 2020
Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs
Yecheng Lyu
Xinming Huang
Ziming Zhang
26
0
0
26 Sep 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng
Hongkuan Zhou
Ajitesh Srivastava
R. Kannan
Viktor Prasanna
GNN
69
948
0
10 Jul 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
Contextual Explanation Networks
Maruan Al-Shedivat
Kumar Avinava Dubey
Eric P. Xing
CML
35
82
0
29 May 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
1