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Deep Representation Learning for Social Network Analysis

Deep Representation Learning for Social Network Analysis

18 April 2019
Qiaoyu Tan
Ninghao Liu
Xia Hu
    AI4TS
    GNN
ArXivPDFHTML

Papers citing "Deep Representation Learning for Social Network Analysis"

10 / 10 papers shown
Title
Marginal Nodes Matter: Towards Structure Fairness in Graphs
Marginal Nodes Matter: Towards Structure Fairness in Graphs
Xiaotian Han
Kaixiong Zhou
Ting-Hsiang Wang
Jundong Li
Fei Wang
Na Zou
27
0
0
23 Oct 2023
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent
  Space Reconstruction
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction
Yucheng Shi
Yushun Dong
Qiaoyu Tan
Jundong Li
Ninghao Liu
40
24
0
18 Aug 2023
Improving Generalizability of Graph Anomaly Detection Models via Data
  Augmentation
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation
Shuang Zhou
Xiao Shi Huang
Ninghao Liu
Huachi Zhou
F. Chung
Longhai Huang
36
23
0
18 Jun 2023
Structural Imbalance Aware Graph Augmentation Learning
Structural Imbalance Aware Graph Augmentation Learning
Zulong Liu
Kejia Chen
Zheng Liu
23
0
0
24 Mar 2023
Graph Contrastive Learning with Personalized Augmentation
Graph Contrastive Learning with Personalized Augmentation
X. Zhang
Qiaoyu Tan
Xiao Shi Huang
Bo-wen Li
33
15
0
14 Sep 2022
Understanding graph embedding methods and their applications
Understanding graph embedding methods and their applications
Mengjia Xu
18
128
0
15 Dec 2020
Auto-Keras: An Efficient Neural Architecture Search System
Auto-Keras: An Efficient Neural Architecture Search System
Haifeng Jin
Qingquan Song
Xia Hu
23
793
0
27 Jun 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,235
0
24 Jun 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs
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
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
244
3,236
0
24 Nov 2016
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