📃 Explainability in Graph Neural Networks: A Taxonomic Survey

📘 Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
🗓 Publish year: 2022

🧑‍💻Authors: Hao Yuan, Haiyang Yu, Shurui Gui, and Shuiwang Ji
🏢University: Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

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📑Can Graph Neural Networks be Adequately Explained? A Survey

📗 Journal: ACM Computing Surveys (🔥I.F.=23.8)
🗓 Publish year: 2025

🧑‍💻Authors: Xuyan Li, Jie Wang, Zheng Yan
🏢University: Xidian University, China

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📑Explaining the Explainers in Graph Neural Networks: a Comparative Study

📕 Journal: ACM Computing Surveys (🔥I.F.=23.8)
🗓 Publish year: 2025

🧑‍💻Authors: Antonio Longa, Steve Azzolin, Gabriele Santin, ...
🏢Universities: University of Trento, Italy - Cambridge University, UK

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📃A Review of Link Prediction Algorithms in Dynamic Networks

📗 Journal: Mathematics (I.F.=2.3)
🗓 Publish year: 2025

🧑‍💻Authors: Mengdi Sun, Minghu Tang
🏢Universities: Qinghai Minzu University, China

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📃Information diffusion analysis: process, model, deployment, and application

📗 Journal:The Knowledge Engineering Review (I.F.=2.8)
🗓 Publish year: 2025

🧑‍💻Authors: Shashank Sheshar Singh, Divya Srivastava, Madhushi Verma, ...
🏢Universities: Thapar Institute of Engineering & Technology, Bennett University, India

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