Preserving Node-level Privacy in Graph Neural Networks

12 November 2023

Papers citing "Preserving Node-level Privacy in Graph Neural Networks"

8 / 8 papers shown

Title
AdvSGM: Differentially Private Graph Learning via Adversarial Skip-gram Model Sen Zhang Qingqing Ye Haibo Hu Jianliang Xu 42 0 0 27 Mar 2025
DP-GPL: Differentially Private Graph Prompt Learning Jing Xu Franziska Boenisch Iyiola Emmanuel Olatunji Adam Dziedzic AAML 45 0 0 13 Mar 2025
Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Sen Zhang Qingqing Ye Haibo Hu 28 0 0 08 Jan 2025
Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services Shaopeng Fu Xuexue Sun Ke Qing Tianhang Zheng Di Wang AAML MIACV SILM 38 0 0 05 Aug 2024
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 131 258 0 13 Oct 2021
Releasing Graph Neural Networks with Differential Privacy Guarantees Iyiola E. Olatunji Thorben Funke Megha Khosla 27 44 0 18 Sep 2021
Locally Differentially Private Analysis of Graph Statistics Jacob Imola Takao Murakami Kamalika Chaudhuri 65 70 0 17 Oct 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 139 828 0 28 Sep 2019