Data Augmentation on Graphs: A Technical Survey

Data Augmentation on Graphs: A Technical Survey

20 December 2022

Xiangyu Zhao

Papers citing "Data Augmentation on Graphs: A Technical Survey"

9 / 9 papers shown

Title
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation Mohammad Hashemi Shengbo Gong Juntong Ni Wenqi Fan B. A. Prakash Wei-dong Jin DD 59 37 0 29 Jan 2024
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation Qianru Zhang Chao Huang Lianghao Xia Zheng Wang Siu-keung Yiu Ruihua Han AI4TS 35 13 0 19 Jun 2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation Shuang Zhou Xiao Shi Huang Ninghao Liu Huachi Zhou F. Chung Longhai Huang 25 22 0 18 Jun 2023
Clarify Confused Nodes via Separated Learning Jiajun Zhou Sheng Gong Chenxuan Xie Shanqing Yu Qi Xuan Xiaoniu Yang Xiaoniu Yang 29 3 0 04 Jun 2023
Learning Graph Augmentations to Learn Graph Representations Kaveh Hassani Amir Hosein Khas Ahmadi 29 17 0 24 Jan 2022
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 48 0 10 Nov 2021
HDMI: High-order Deep Multiplex Infomax Baoyu Jing Chanyoung Park Hanghang Tong 93 140 0 15 Feb 2021
Robust Optimization as Data Augmentation for Large-scale Graphs Kezhi Kong G. Li Mucong Ding Zuxuan Wu Chen Zhu Bernard Ghanem Gavin Taylor Tom Goldstein 87 74 0 19 Oct 2020
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 151 25,150 0 09 Jun 2011