π Machine Learning with Graphs: design space of graph neural networks
π₯Free recorded course by Prof. Jure Leskovec
π₯ This part discussed the important topic of GNN architecture design. Here, we introduce 3 key aspects in GNN design: (1) a general GNN design space, which includes intra-layer design, inter-layer design and learning configurations; (2) a GNN task space with similarity metrics so that we can characterize different GNN tasks and, therefore, transfer the best GNN models across tasks; (3) an effective GNN evaluation technique so that we can convincingly evaluate any GNN design question, such as βIs BatchNorm generally useful for GNNs?β. Overall, we provide the first systematic investigation of general guidelines for GNN design, understandings of GNN tasks, and how to transfer the best GNN designs across tasks. We release GraphGym as an easy-to-use code platform for GNN architectural design. More information can be found in the paper: Design Space for Graph Neural Networks
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning
π₯Free recorded course by Prof. Jure Leskovec
π₯ This part discussed the important topic of GNN architecture design. Here, we introduce 3 key aspects in GNN design: (1) a general GNN design space, which includes intra-layer design, inter-layer design and learning configurations; (2) a GNN task space with similarity metrics so that we can characterize different GNN tasks and, therefore, transfer the best GNN models across tasks; (3) an effective GNN evaluation technique so that we can convincingly evaluate any GNN design question, such as βIs BatchNorm generally useful for GNNs?β. Overall, we provide the first systematic investigation of general guidelines for GNN design, understandings of GNN tasks, and how to transfer the best GNN designs across tasks. We release GraphGym as an easy-to-use code platform for GNN architectural design. More information can be found in the paper: Design Space for Graph Neural Networks
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning
arXiv.org
Design Space for Graph Neural Networks
The rapid evolution of Graph Neural Networks (GNNs) has led to a growing number of new architectures as well as novel applications. However, current research focuses on proposing and evaluating...
πΉCreating a Social Network with ChatGPT
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #chatgpt
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #chatgpt
YouTube
Creating a Social Network with ChatGPT
Website: https://thenewboston.com/
Source Code: https://github.com/thenewboston-developers
Core Deployment Guide: https://docs.google.com/document/d/16NDHWtmwmsnrACytRXp2T9Jg7R5FgzRmkYoDteFKxyc/edit?usp=sharing
Source Code: https://github.com/thenewboston-developers
Core Deployment Guide: https://docs.google.com/document/d/16NDHWtmwmsnrACytRXp2T9Jg7R5FgzRmkYoDteFKxyc/edit?usp=sharing
πStochastic Block Models for Complex Network Analysis: A Survey
π Publish year: 2024
πJournal: ACM Transactions on Knowledge Discovery from Data (I.F=4)
π§βπ»Authors: Xueyan Liu, Wenzhuo Song, Katarzyna Musial, Yang Li, Xuehua Zhao, Bo Yang
π’Universities: Jilin University, Northeast Normal University, University of Technology Sydney, Aviation University of Air Force, Shenzhen Institute of Information Technology, Jilin University
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Stochastic #Block #review
π Publish year: 2024
πJournal: ACM Transactions on Knowledge Discovery from Data (I.F=4)
π§βπ»Authors: Xueyan Liu, Wenzhuo Song, Katarzyna Musial, Yang Li, Xuehua Zhao, Bo Yang
π’Universities: Jilin University, Northeast Normal University, University of Technology Sydney, Aviation University of Air Force, Shenzhen Institute of Information Technology, Jilin University
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Stochastic #Block #review
π Graph Data Management and Graph Machine Learning: Synergies and Opportunities
π Publish year: 2025
π§βπ»Authors: Arijit Kha, Xiangyu Ke, Yinghui Wu
π’University:
- Aalborg University, Denmark
- Zhejiang University, China
- Case Western Reserve University, USA
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #graph #machine_learning #data_management
π Publish year: 2025
π§βπ»Authors: Arijit Kha, Xiangyu Ke, Yinghui Wu
π’University:
- Aalborg University, Denmark
- Zhejiang University, China
- Case Western Reserve University, USA
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #graph #machine_learning #data_management
π1
πCounterfactual Learning on Graphs: A Survey
π Publish year: 2025
πJournal: Machine Intelligence Research
π§βπ»Authors: Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal , Hui Liu, Suhang Wang
π’Universities: Pennsylvania State University, Watson Research Center
π Study paper
π²Channel: @ComplexNetworkAnalysis
#paper #Counterfactual #Survey
π Publish year: 2025
πJournal: Machine Intelligence Research
π§βπ»Authors: Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal , Hui Liu, Suhang Wang
π’Universities: Pennsylvania State University, Watson Research Center
π Study paper
π²Channel: @ComplexNetworkAnalysis
#paper #Counterfactual #Survey
π A curated list of awesome network analysis resources
π₯ GitBook website
π Study
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#github #graph #visualization #book
π₯ GitBook website
π Study
β‘οΈChannel: @ComplexNetworkAnalysis
#github #graph #visualization #book
πBibliometric and visualized analysis of social network analysis research on Scopus databases and VOSviewer
π Publish year: 2024
πJournal: Cogent Business & Management (I.F=3)
π§βπ»Authors: Dyah gandasari, David tjahjana, Diena Dwidienawati and Mochamad Sugiarto
π’Universities: Polbangtan Bogor, Bogor, indonesia; universitas Multimedia nusantara, Jakarta, indonesia; Business Management, BinusBusiness school, Bina nusantara university, Jakarta, indonesia; Faculty of animal science, Jendral soedirman university,indonesia
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Bibliometric #Scopus #VOSviewer
π Publish year: 2024
πJournal: Cogent Business & Management (I.F=3)
π§βπ»Authors: Dyah gandasari, David tjahjana, Diena Dwidienawati and Mochamad Sugiarto
π’Universities: Polbangtan Bogor, Bogor, indonesia; universitas Multimedia nusantara, Jakarta, indonesia; Business Management, BinusBusiness school, Bina nusantara university, Jakarta, indonesia; Faculty of animal science, Jendral soedirman university,indonesia
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Bibliometric #Scopus #VOSviewer
π2
πA Survey on Exploring Real and Virtual Social Network Rumors: State-of-the-Art and Research Challenges
π Journal: ACM Computing Surveys (π₯I.F.=23.8)
π Publish year: 2025
π§βπ»Authors: Qiang He, Songyangjun Zhang, Yuliang Cai, ...
π’Universities:
β«οΈNortheastern University-Liaoning University-The First Hospital of China Medical University, China
β«οΈWaseda University, Japan
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #rumor
π Journal: ACM Computing Surveys (π₯I.F.=23.8)
π Publish year: 2025
π§βπ»Authors: Qiang He, Songyangjun Zhang, Yuliang Cai, ...
π’Universities:
β«οΈNortheastern University-Liaoning University-The First Hospital of China Medical University, China
β«οΈWaseda University, Japan
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #rumor
π Methods of decomposition theory and graph labeling in the study of social network structure
π Publish year: 2024
π§βπ»Authors: L Hulianytskyi, M Semeniuta, S Yakymenko
π’Universities: Prospekt Universytetskyi,Ukraine
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #graph_labling #decomposition
π Publish year: 2024
π§βπ»Authors: L Hulianytskyi, M Semeniuta, S Yakymenko
π’Universities: Prospekt Universytetskyi,Ukraine
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #graph_labling #decomposition
β€1π1
2023_A_Survey_of_Large_scale_Complex_Information_Network_Representation.pdf
4.2 MB
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
π1
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
π1
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
π1
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
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