📃Artificial Intelligence for Complex Network: Potential,
Methodology and Application

🗓 Publish year: 2024

🧑‍💻Authors: Jingtao Ding, Chang Liu, Yu Zheng, Yunke Zhang, Zihan Yu, Ruikun Li, Hongyi Chen, Jinghua Piao, Huandong Wang, Jiazhen Liu, Yong Li
🏢Universities: Tsinghua University, Beijing National Research Center for Information Science and Technology (BNRist)China

📎 Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #AI #Application

📃Network Modeling and Control of Dynamic Disease Pathways, Review and Perspectives

📘Journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics (I.F.=3.6)
🗓Publish year: 2024

🧑‍💻Authors: Yen-Che Hsiao; Abhishek Dutta
🏢University: University of Connecticut, USA

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📲Channel: @Bioinformatics
#review #pathway #network

📄Getting started with graph analysis in Python with pandas and networkx

💥Technical Paper

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📲Channel: @ComplexNetworkAnalysis

#paper #Graph #Python #code

🎓Graph Data Science and machine learning applications

📕Master Degree Thesis by Antonella Cardillo form POLITECNICO DI TORINO

🗓Publish year: 2024

📎 Study thesis

📲Channel: @ComplexNetworkAnalysis
#thesis #Graph #machine_learning #Data_Science

📄Network Analysis Visualization

💥Technical Paper

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📲Channel: @ComplexNetworkAnalysis

#paper #Graph #Python #code #Visualization

🎞 Social Networks and Health 2024

💥Free recorded tutorial on social network

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📱Channel: @ComplexNetworkAnalysis
#video #Health

📃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

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📱Channel: @ComplexNetworkAnalysis
#paper #Propagation_Models #Deterministic #Deep_learning #review

📃Understanding Graph Databases: A Comprehensive Tutorial and Survey

🗓 Publish year: 2024

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

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📱Channel: @ComplexNetworkAnalysis
#paper #Graph #Database #Tutorial #survey

📄Graph visualization: an in-depth guide

💥Technical paper from Cambridge Intelligence

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📲Channel: @ComplexNetworkAnalysis
#visualization

📄How Graph Neural Networks Facilitate Social Network Analysis

💥Technical Paper

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📲Channel: @ComplexNetworkAnalysis

#paper #Graph #GNN

📃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.

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📱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

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⚡️Channel: @ComplexNetworkAnalysis
#review #spatial

📃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

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📲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

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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Mapping #Landscape #Applications

📹Exploring Instagram’s Top 100 Influencers with Gephi: Social Network Analysis & Community Mapping

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⚡️Channel: @ComplexNetworkAnalysis
#video #gephi #instagram

📃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

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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #SelfSupervised

🎞 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.

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📱Channel: @ComplexNetworkAnalysis
#video #GNN #Application