2023_A_Survey_of_Large_scale_Complex_Information_Network_Representation.pdf
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πA Survey of Large-scale Complex Information Network Representation Learning Methods
π Publish year: 2023
πConference: Consumer Electronics and Computer Engineering (ICCECE)
π§βπ»Authors: Xiaoxian Zhang
π’Universities: School of Computer Technology and Engineering Changchun Institute of Technology, Changchun, China
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Large_scale #Complex #Information #Representation_Learning #survey
π Publish year: 2023
πConference: Consumer Electronics and Computer Engineering (ICCECE)
π§βπ»Authors: Xiaoxian Zhang
π’Universities: School of Computer Technology and Engineering Changchun Institute of Technology, Changchun, China
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Large_scale #Complex #Information #Representation_Learning #survey
π₯ Knowledge graphs - Foundations and applications
π Watch the collection
β‘οΈChannel: @ComplexNetworkAnalysis
#video #knowledge_graph
π Watch the collection
β‘οΈChannel: @ComplexNetworkAnalysis
#video #knowledge_graph
πExplaining the Explainers in Graph Neural Networks: a Comparative Study
π Journal: ACM Computing Surveys (π₯I.F.=23.8)
π Publish year: 2025
π§βπ»Authors: Antonio Longa, Steve Azzolin, Gabriele Santin, ...
π’Universities: University of Trento, Italy - Cambridge University, UK
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
π Journal: ACM Computing Surveys (π₯I.F.=23.8)
π Publish year: 2025
π§βπ»Authors: Antonio Longa, Steve Azzolin, Gabriele Santin, ...
π’Universities: University of Trento, Italy - Cambridge University, UK
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
πNetwork link prediction via deep learning method: A comparative analysis with traditional methods
π Publish year: 2024
πJournal: Engineering Science and Technology, an International Journal (I.F=5.1)
π§βπ»Authors: Gholamreza Zare, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Amir Sahafi
π’Universities: Islamic Azad University, Qeshm Branch, Qeshm, Iran
Islamic Azad University, Tabriz Branch, Tabriz, Iran
National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan
Western Caspian University, Baku, Azerbaijan
Duy Tan University, Da Nang, Viet Nam
Duy Tan University, School of Medicine and Pharmacy, Da Nang, Viet Nam
Islamic Azad University, South Tehran Branch, Tehran, Iran
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #Deep_learning #traditional
π Publish year: 2024
πJournal: Engineering Science and Technology, an International Journal (I.F=5.1)
π§βπ»Authors: Gholamreza Zare, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Amir Sahafi
π’Universities: Islamic Azad University, Qeshm Branch, Qeshm, Iran
Islamic Azad University, Tabriz Branch, Tabriz, Iran
National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan
Western Caspian University, Baku, Azerbaijan
Duy Tan University, Da Nang, Viet Nam
Duy Tan University, School of Medicine and Pharmacy, Da Nang, Viet Nam
Islamic Azad University, South Tehran Branch, Tehran, Iran
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #Deep_learning #traditional
π Algorithms and Graph Structures for Splitting Network Flows, in Theory and Practice
πPhD thesis from University of Helsinki, Finland
πPublish year: 2025
π Study thesis
β‘οΈChannel: @ComplexNetworkAnalysis
#thesis #network_flow
πPhD thesis from University of Helsinki, Finland
πPublish year: 2025
π Study thesis
β‘οΈChannel: @ComplexNetworkAnalysis
#thesis #network_flow
π A Survey of Graph Transformers: Architectures, Theories and Applications
π Publish year: 2025
π§βπ»Authors: Chaohao Yuan, Kangfei Zhao, Ercan Engin Kuruoglu, ...
π’Universities: Tsinghua University - Chinese University of Hong Kong - Chinese Academy of Sciences, China
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #transformer
π Publish year: 2025
π§βπ»Authors: Chaohao Yuan, Kangfei Zhao, Ercan Engin Kuruoglu, ...
π’Universities: Tsinghua University - Chinese University of Hong Kong - Chinese Academy of Sciences, China
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #transformer
π Node centrality metric and link analysis
π₯Social Network Analysis Lecture 3
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Node #centerality #link
π₯Social Network Analysis Lecture 3
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Node #centerality #link
YouTube
Social Network Analysis Lecture 3. Node centrality metric and link analysis.
π Machine Learning with Graphs: GraphSAGE Neighbor Sampling
π₯Free recorded course by Prof. Jure Leskovec
π₯ This part discussed Neighbor Sampling, That is a representative method used to scale up GNNs to large graphs. The key insight is that a K-layer GNN generates a node embedding by using only the nodes from the K-hop neighborhood around that node. Therefore, to generate embeddings of nodes in the mini-batch, only the K-hop neighborhood nodes and their features are needed to load onto a GPU, a tractable operation even if the original graph is large. To further reduce the computational cost, only a subset of neighboring nodes is sampled for GNNs to aggregate.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #GraphSAGE
π₯Free recorded course by Prof. Jure Leskovec
π₯ This part discussed Neighbor Sampling, That is a representative method used to scale up GNNs to large graphs. The key insight is that a K-layer GNN generates a node embedding by using only the nodes from the K-hop neighborhood around that node. Therefore, to generate embeddings of nodes in the mini-batch, only the K-hop neighborhood nodes and their features are needed to load onto a GPU, a tractable operation even if the original graph is large. To further reduce the computational cost, only a subset of neighboring nodes is sampled for GNNs to aggregate.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #GraphSAGE
YouTube
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.2 - GraphSAGE Neighbor Sampling
For more information about Stanfordβs Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Brn5kW
Lecture 17.2 - GraphSAGE Neighbor Sampling Scaling up GNNs
Jure Leskovec
Computer Science, PhD
Neighbor Sampling is a representativeβ¦
Lecture 17.2 - GraphSAGE Neighbor Sampling Scaling up GNNs
Jure Leskovec
Computer Science, PhD
Neighbor Sampling is a representativeβ¦
πA Review of Link Prediction Algorithms in Dynamic Networks
π Journal: Mathematics (I.F.=2.3)
π Publish year: 2025
π§βπ»Authors: Mengdi Sun, Minghu Tang
π’Universities: Qinghai Minzu University, China
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
π Journal: Mathematics (I.F.=2.3)
π Publish year: 2025
π§βπ»Authors: Mengdi Sun, Minghu Tang
π’Universities: Qinghai Minzu University, China
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
Forwarded from Bioinformatics
π Graph Neural Network-Based Approaches to Drug Repurposing: A Comprehensive Survey
π Publish year: 2025
π§βπ»Authors: Alireza A.Tabatabaei, Mohammad Ebrahim Mahdavi, Ehsan Beiranvand, ...
π’Universities: University of Isfahan, Shahid Beheshti University of Medical Sciences, University of Tehran - Iran
π Study the paper
π²Channel: @Bioinformatics
#review #drug #repurposing #gnn
π Publish year: 2025
π§βπ»Authors: Alireza A.Tabatabaei, Mohammad Ebrahim Mahdavi, Ehsan Beiranvand, ...
π’Universities: University of Isfahan, Shahid Beheshti University of Medical Sciences, University of Tehran - Iran
π Study the paper
π²Channel: @Bioinformatics
#review #drug #repurposing #gnn
πData Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook
π Publish year: 2025
π§βπ»Authors: Jiawei Xue, Ruichen Tan, Jianzhu Ma, Satish V. Ukkusuri
π’Universities: Purdue University, West Lafayette, IN, USA.
Tsinghua University, Beijing, China.
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Data_Mining #Transportation #GNN #review
π Publish year: 2025
π§βπ»Authors: Jiawei Xue, Ruichen Tan, Jianzhu Ma, Satish V. Ukkusuri
π’Universities: Purdue University, West Lafayette, IN, USA.
Tsinghua University, Beijing, China.
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Data_Mining #Transportation #GNN #review
π Introduction to Random Graphs
π₯ Free online book by Carnegie Mellon University, 2025
π Study
β‘οΈChannel: @ComplexNetworkAnalysis
#book #graph #random
π₯ Free online book by Carnegie Mellon University, 2025
π Study
β‘οΈChannel: @ComplexNetworkAnalysis
#book #graph #random
πInformation diffusion analysis: process, model, deployment, and application
π Journal:The Knowledge Engineering Review (I.F.=2.8)
π Publish year: 2025
π§βπ»Authors: Shashank Sheshar Singh, Divya Srivastava, Madhushi Verma, ...
π’Universities: Thapar Institute of Engineering & Technology, Bennett University, India
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
π Journal:The Knowledge Engineering Review (I.F.=2.8)
π Publish year: 2025
π§βπ»Authors: Shashank Sheshar Singh, Divya Srivastava, Madhushi Verma, ...
π’Universities: Thapar Institute of Engineering & Technology, Bennett University, India
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #explainability #gnn
π Introduction to Social Network Analysis
π₯This session is part of the ESRC Centre for Society and Mental Health's Research Methods Primer and Provocation series.
π₯In this session, Dr Molly Copeland and Holly Crudgington provide an introduction to social network analysis (SNA) with a focus on major theories and conceptual approaches to using ego-centric and sociometric network data for those new to considering networks.
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video
π₯This session is part of the ESRC Centre for Society and Mental Health's Research Methods Primer and Provocation series.
π₯In this session, Dr Molly Copeland and Holly Crudgington provide an introduction to social network analysis (SNA) with a focus on major theories and conceptual approaches to using ego-centric and sociometric network data for those new to considering networks.
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video
YouTube
Introduction to Social Network Analysis
This session is part of the ESRC Centre for Society and Mental Health's Research Methods Primer and Provocation series.
In this session, Dr Molly Copeland and Holly Crudgington provide an introduction to social network analysis (SNA) with a focus on majorβ¦
In this session, Dr Molly Copeland and Holly Crudgington provide an introduction to social network analysis (SNA) with a focus on majorβ¦