GraphGuard: Detecting and Counteracting Training Data Misuse in Graph
Neural Networks

GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks

13 December 2023

Shuo Wang

Papers citing "GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks"

8 / 8 papers shown

Title
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang Yixin Liu Xu Shen Chenyu Li Kaize Ding Rui Miao Ying Wang Shirui Pan Xin Wang 32 8 0 21 Jun 2024
Online GNN Evaluation Under Test-time Graph Distribution Shifts Xin-Yang Zheng Dongjin Song Qingsong Wen Bo Du Shirui Pan 29 6 0 15 Mar 2024
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning Man Wu Xin-Yang Zheng Qin Zhang Xiao Shen Xiong Luo Xingquan Zhu Shirui Pan OOD 65 6 0 26 Feb 2024
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks He Zhang Xingliang Yuan Shirui Pan 18 11 0 30 Jan 2023
A Survey of Machine Unlearning Thanh Tam Nguyen T. T. Huynh Phi Le Nguyen Alan Wee-Chung Liew Hongzhi Yin Quoc Viet Hung Nguyen MU 77 216 0 06 Sep 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 98 0 16 May 2022
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 34 96 0 17 Jan 2021
Stealing Links from Graph Neural Networks Xinlei He Jinyuan Jia Michael Backes Neil Zhenqiang Gong Yang Zhang AAML 53 164 0 05 May 2020