Network Analysis Resources & Updates – Telegram
Network Analysis Resources & Updates
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📃A Survey on Graph Neural Networks for Intrusion Detection Systems: Methods, Trends and Challenges

🗓 Publish year: 2024
📘
Journal: Computers & Security (I.F=4.8)

🧑‍💻Authors: Meihui Zhong, Mingwei Lin, Chao Zhang, Zeshui Xu
🏢Universities: Fujian Normal University, Fuzhou, 350117, Fujian, China.
Shanxi University, Taiyuan, 030006, Shanxi, China.
Sichuan University, Chengdu, 610064, Sichuan, China
.

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Intrusion_Detection_Systems #Trends #Challenges #survey
👍3
📃A Comprehensive Review of Propagation Models in Complex Networks: From Deterministic to Deep Learning Approaches

🗓 Publish year: 2024
🧑‍💻Authors: Bin Wu, Sifu Luo and C. Steve Suh

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Propagation_Models #Deterministic #Deep_learning #review
🔥2
📃Understanding Graph Databases: A Comprehensive Tutorial and Survey

🗓 Publish year: 2024

🧑‍💻Authors: Sydney Anuyah, Emmanuel Bolade, Oluwatosin Agbaakin
🏢Universities: Indiana University, Indianapolis, IN, USA

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Graph #Database #Tutorial #survey
👍1
📄Graph visualization: an in-depth guide

💥Technical paper from Cambridge Intelligence


🌐 Study

📲Channel: @ComplexNetworkAnalysis
#visualization
📃Network analysis and teaching excellence as a concept of relations

🗓 Publish year: 2024
📘
Journal: Teaching in Higher Education (I.F=2.4)

🧑‍💻Authors: Aneta Hayes, Nick Garnett
🏢Universities: Keele University, Keele, UK.
Nottingham Trent University, Nottingham, UK.


📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #teaching #excellence #relations
📃Research on Topological Characteristics of Spatial Network Based on Complex Network Theory and Its Applications

🗓 Publish year: 2024
📔Journal: Mathematics (I.F=2.3)

🧑‍💻Authors: Siqin Su, Jintao Liu,Yongqi Wang, ...
🏢Universities: Civil Aviation University of China, China

📎 Study paper

⚡️Channel: @ComplexNetworkAnalysis
#review #spatial
👍1
A survey of data efficient graph learning .pdf
225.1 KB
📃A survey of data efficient graph learning

🗓 Publish year: 2024

🧑‍💻Authors: Wei Ju, Siyu Yi , Yifan Wang , Qingqing Long , Junyu Luo , Zhiping Xiao , Ming Zhang
🏢Universities: Peking University, Nankai University,University of California Los Angeles

📎 Study paper

📲Channel: @ComplexNetworkAnalysis
#paper #Graph #data #Survey
📃Graph Neural Networks: A Bibliometric Mapping of the Research Landscape and Applications

🗓 Publish year: 2024
📘
Journal: Information (I.F=2.4)

🧑‍💻Authors: Annielle Mendes Brito da Silva, Natiele Carla da Silva Ferreira, Luiza Amara Maciel Braga, Fabio Batista Mota, Victor Maricato, Luiz Anastacio Alves
🏢Universities: Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Pontifical Catholic University of Rio de Janeiro, Karolinska Institutet

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Mapping #Landscape #Applications
1
Self-Supervised Temporal Graph Learning .pdf
928 KB
📃Self-Supervised Temporal Graph Learning with Temporal and Structural Intensity Alignment

🗓 Publish year: 2024

🧑‍💻Authors: Meng Liu, Ke Liang, Yawei Zhao, Wenxuan Tu, Sihang Zhou، Xinbiao Gan, Xinwang Liu
🏢Universities: National University of Defense Technology

📎 Study paper

📲Channel: @ComplexNetworkAnalysis
#paper #Graph #SelfSupervised
2
🎞 An Introduction to Graph Neural Networks: Models and Applications

💥Free Recorded Lecture on Applications of Graph Neural Networks.
🔹Graph Neural Networks (GNN) are a general class of networks that work over graphs. By representing a problem as a graph — encoding the information of individual elements as nodes and their relationships as edges — GNNs learn to capture patterns within the graph. These networks have been successfully used in applications such as chemistry and program analysis. In this introductory talk, I will do a deep dive in the neural message-passing GNNs, and show how to create a simple GNN implementation.

📽 Watch

📱Channel: @ComplexNetworkAnalysis
#video #GNN #Application
👍1
🎓Ensemble approaches for Link Prediction

📕MSc thesis from The University in Stuttgart, Germany

🗓Publish year: 2024

📎 Study thesis

⚡️Channel: @ComplexNetworkAnalysis
#thesis #link_prediction
👍1
Machine Learning for Refining Knowledge Graph.pdf
2.4 MB
📃Machine Learning for Refining Knowledge Graphs: A Survey

🗓 Publish year: 2024

🧑‍💻Authors: BUDHITAMA SUBAGDJA, D. SHANTHOSHIGAA, ZHAOXIA WANG, and AH-HWEE TAN
🏢Universities: Singapore Management University

📎 Study paper

📲Channel: @ComplexNetworkAnalysis
#paper #Graph #ML #Survey
👍2
📃Current and future directions in network biology

🗓 Publish year: 2023
📘
Journal: Bioinformatics Advances (I.F=2.4)

🧑‍💻Authors: Marinka Zitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, ...

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Biology #Direction
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📃Self-Supervised Learning for Graph-Structured Data in Healthcare Applications: A Comprehensive Review

🗓 Publish year: 2024

🧑‍💻Authors: Safa Ben Atitallah, Chaima Ben Rabah, Maha Driss, ...
🏢
Universities: Prince Sultan University, Saudi Arabia - University of Manouba, Manouba , Tunisia

📎 Study paper

⚡️Channel: @ComplexNetworkAnalysis
#review #self_supervised #gnn