GraphSAC: Detecting anomalies in large-scale graphs

21 October 2019

Papers citing "GraphSAC: Detecting anomalies in large-scale graphs"

9 / 9 papers shown

Title
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning Vasudev Gohil Satwik Patnaik D. Kalathil Jeyavijayan Rajendran AAML 65 3 0 21 Feb 2024
Adversarial Camouflage for Node Injection Attack on Graphs Shuchang Tao Qi Cao Huawei Shen Yunfan Wu Liang Hou Fei Sun Xueqi Cheng AAML GNN 35 22 0 03 Aug 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Lizhen Qu Shirui Pan Hanghang Tong Jian Pei 47 104 0 16 May 2022
Model Stealing Attacks Against Inductive Graph Neural Networks Yun Shen Xinlei He Yufei Han Yang Zhang 29 62 0 15 Dec 2021
Decentralized Inference with Graph Neural Networks in Wireless Communication Systems Mengyuan Lee Guanding Yu H. Dai GNN 55 41 0 19 Apr 2021
GraphAttacker: A General Multi-Task GraphAttack Framework Jinyin Chen Dunjie Zhang Zhaoyan Ming Kejie Huang Wenrong Jiang Chen Cui AAML 41 14 0 18 Jan 2021
Unsupervised Adversarially-Robust Representation Learning on Graphs Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Yizhou Sun SSL AAML OOD 43 36 0 04 Dec 2020
Graph Signal Processing -- Part III: Machine Learning on Graphs, from Graph Topology to Applications Ljubisa Stankovic Danilo P. Mandic M. Daković M. Brajović Bruno Scalzo Shengxi Li A. Constantinides 36 23 0 02 Jan 2020
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He Yangqiu Song GNN AAML 28 276 0 26 Dec 2018