📃Graph Machine Learning in the Era of Large Language Models (LLMs)

🗓 Publish year: 2023

🧑‍💻Authors: Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li

🏢Universities: The Hong Kong Polytechnic University,Michigan State University, North Carolina State University

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📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Machine_Learning #LLMs

📃Federated Graph Neural Networks: Overview, Techniques, and Challenges

🗓 Publish year: 2024
📘 Journal: IEEE Transactions on Neural Networks and Learning Systems (I.F=14.255)

🧑‍💻Authors: Rui Liu , Pengwei Xing , Zichao Deng, Anran Li , Cuntai Guan , Fellow, IEEE, and Han Yu
🏢Universities: Nanyang Technological University

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📲Channel: @ComplexNetworkAnalysis
#paper #Federated_Graph_Neural_Networks #Challenges #Techniques #Overview

🎞 Machine Learning with Graphs: Pre-Training Graph Neural Networks

💥Free recorded course by Prof. Jure Leskovec

💥There are two challenges in applying GNNs to scientific domains: scarcity of labeled data and out-of-distribution prediction. In this video we discuss methods for pre-training GNNs to resolve these challenges. The key idea is to pre-train both node and graph embeddings, which leads to significant performance gains on downstream tasks.

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📑More details can be found in the paper: Strategies for Pre-training Graph Neural Networks

📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning

📃A Survey on Graph Representation Learning Methods

🗓 Publish year: 2024
📘 Journal: ACM Transactions on Intelligent Systems and Technology (I.F=10.489)

🧑‍💻Authors: Shima Khoshraftar, Aijun An
🏢Universities: York University

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📲Channel: @ComplexNetworkAnalysis
#paper #Survey #GNN

📃 Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

🗓 Publish year: 2022
📘Conference: International Joint Conference on Artificial Intelligence

🧑‍💻Authors: Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye,Dongrui Fan, Shirui Pan, Yuan Xie
🏢Universities: University of Chinese Academy of Sciences,Tsinghua University, Monash University, University of California

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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Acceleration #Algorithmic #Perspective #survey

📃 A Survey of Graph Pre-processing Methods: From Algorithmic to Hardware Perspectives

🗓 Publish year: 2023

🧑‍💻Authors: Zhengyang Lv, Mingyu Yan, Xin Liu, Mengyao Dong, Xiaochun Ye, Dongrui Fan, Ninghui Sun
🏢University: ShanghaiTech Univ, China and SHIC, China

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📱Channel: @ComplexNetworkAnalysis
#paper #Graph #Pre_processing #Algorithm #Hardware #Perspectives #survey

📃 Graph Neural Network-based EEG Classification: A Survey

🗓 Publish year: 2023

🧑‍💻Authors: Dominik Klepl, Min Wu, and Fei He
🏢University: Coventry University

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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #EEG #Classification #survey

📃 Emerging landscape of molecular interaction networks:
Opportunities, challenges and prospects

🗓 Publish year: 2022
📘Journal: Journal of Biosciences(I.F=2.9)

🧑‍💻Authors: Gauri Panditrao, Rupa Bhowmick, Chandrakala Meena and Ram Rup Sarka
🏢University: Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India

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📱Channel: @ComplexNetworkAnalysis
#paper #Emerging #landscape #molecular #Opportunities #challenges #prospects

🎞Community detection (clustering network data) and modularity

💥Free recorded course by Prof. Samin Aref

💥Community detection (clustering network data), optimization-based community detection, Zachary Karate club, modularity function, maximum-modularity partitions, optimal partitions

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📲Channel: @ComplexNetworkAnalysis
#video #Graph #Community_detection #modularity