๐Knowledge Graph Completion: A Birdโs Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Knowledge_Graphs #Embeddings #Software #Applications #Challenges
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Knowledge_Graphs #Embeddings #Software #Applications #Challenges
๐ Machine Learning with Graphs: PageRank Random Walks and embedding
๐ฅFree recorded course by Jure Leskovec, Computer Science, PhD
๐ฅIn this lecture, -we will talk about an alternative approach, message passing. We will introduce the semi-supervised learning on predicting node labels by leveraging correlations that exist in the network. One key concept is the collective classification, which involves three steps including the local classifier that assigns initial labels, the relational classifier that captures correlations, and the collective inference that propagates correlations.
-we introduce belief propagation, which is a dynamic programming approach to answering probability queries in a graph. By iteratively passing messages to neighbors, the final belief is calculated if a consensus is reached. We then show the message passing with examples and generalization to tree structure. At last, we talk about the loopy belief propagation algorithm, and its pros and cons.
-we introduce the relational classifier and iterative classification for node classification. Starting from the relational classifier, we show how to iteratively update probabilities of node labels based on the labels of neighbors. We then talk about the iterative classification that improves the collective classification by predicting node label based on labels of neighbors as well as its features
๐ฝ Watch: part1 part2 part3
๐ฒChannel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
๐ฅFree recorded course by Jure Leskovec, Computer Science, PhD
๐ฅIn this lecture, -we will talk about an alternative approach, message passing. We will introduce the semi-supervised learning on predicting node labels by leveraging correlations that exist in the network. One key concept is the collective classification, which involves three steps including the local classifier that assigns initial labels, the relational classifier that captures correlations, and the collective inference that propagates correlations.
-we introduce belief propagation, which is a dynamic programming approach to answering probability queries in a graph. By iteratively passing messages to neighbors, the final belief is calculated if a consensus is reached. We then show the message passing with examples and generalization to tree structure. At last, we talk about the loopy belief propagation algorithm, and its pros and cons.
-we introduce the relational classifier and iterative classification for node classification. Starting from the relational classifier, we show how to iteratively update probabilities of node labels based on the labels of neighbors. We then talk about the iterative classification that improves the collective classification by predicting node label based on labels of neighbors as well as its features
๐ฝ Watch: part1 part2 part3
๐ฒChannel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
YouTube
Stanford CS224W: ML with Graphs | 2021 | Lecture 5.1 - Message passing and Node Classification
For more information about Stanfordโs Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3jHRiGj
Jure Leskovec
Computer Science, PhD
From previous lectures, we learn the use of graph representation learning for node classification.โฆ
Jure Leskovec
Computer Science, PhD
From previous lectures, we learn the use of graph representation learning for node classification.โฆ
๐Taxonomy of Link Prediction for Social Network Analysis: A Review
๐Journal: IEEE Access (I.F=3.476)
๐Publish year: 2020
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Taxonomy #Link_Prediction #review
๐Journal: IEEE Access (I.F=3.476)
๐Publish year: 2020
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Taxonomy #Link_Prediction #review
๐Knowledge graph and knowledge reasoning: A systematic review
๐Journal: Journal of Electronic Science and Technology
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Knowledge_graph #review
๐Journal: Journal of Electronic Science and Technology
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Knowledge_graph #review
Knowledge_Graph_Embedding_A_Survey_of_Approaches_and_Applications.pdf
970.4 KB
๐Knowledge Graph Embedding: A Survey of Approaches and Applications
๐Journal: IEEE Transactions on Knowledge and Data Engineering(I.F=6.997)
๐Publish year: 2017
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper
๐Journal: IEEE Transactions on Knowledge and Data Engineering(I.F=6.997)
๐Publish year: 2017
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper
๐Gamification in education: A citation network analysis using
CitNetExplorer
๐Journal: Contemporary Educational Technology(I.F=3.68)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #CitNetExplorer
CitNetExplorer
๐Journal: Contemporary Educational Technology(I.F=3.68)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #CitNetExplorer
๐Complex Network Analysis of China National Standards for New Energy Vehicles
๐Journal: Sustainability(I.F=3.889)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper
๐Journal: Sustainability(I.F=3.889)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper
๐จโ๐ป MSc position at SBNA (Social & Biological Network Analysis) Lab
๐ฎ๐ท Language: IR
๐ Details
๐ฒChannel: @ComplexNetworkAnalysis
๐ฎ๐ท Language: IR
๐ Details
๐ฒChannel: @ComplexNetworkAnalysis
๐A Mini review of Node Centrality Metrics in Biological Networks
๐Journal: International Journal of Network Dynamics and Intelligence
๐Publish year: 2022
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #centrality #biological
๐Journal: International Journal of Network Dynamics and Intelligence
๐Publish year: 2022
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #centrality #biological
๐ Knowledge Graph Seminar Session 1 (Spring 2020)
๐ฅFree recorded tutorial on Knowledge Graph.
๐ฝWatch
๐ฑChannel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
๐ฅFree recorded tutorial on Knowledge Graph.
๐ฝWatch
๐ฑChannel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
YouTube
CS520: Knowledge Graph Seminar Session 1 (Spring 2020)
What is a Knowledge Graph?
๐A Network Science perspective of Graph Convolutional Networks: A survey
๐Journal: FUTURE INTERNET
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #perspective #Convolutional #survey
๐Journal: FUTURE INTERNET
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #perspective #Convolutional #survey
๐Network Analysis of Road Traffic Crash and Rescue Operations in Federal Capital City
๐Journal: International Journal of Geosciences (I.F=1.525)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Traffic
๐Journal: International Journal of Geosciences (I.F=1.525)
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Traffic
๐Graph-based Time-Series Anomaly Detection: A Survey
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Time_Series #Anomaly #survey
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Time_Series #Anomaly #survey
๐Women financial inclusion research: a bibliometric and network analysis
๐Journal: INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Women #financial #inclusion #bibliometric
๐Journal: INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Women #financial #inclusion #bibliometric
๐Predicting the establishment and removal of global trade relations for import and export of petrochemical products
๐Journal: Energy (I.F=8.857)
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #prediction #trade #petrochemical
๐Journal: Energy (I.F=8.857)
๐Publish year: 2023
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #prediction #trade #petrochemical
๐ Graph Theory Algorithms
๐ฅA complete overview of graph theory algorithms in computer science and mathematics.
๐ฝWatch
๐ฒChannel: @ComplexNetworkAnalysis
#video #Graph #course
๐ฅA complete overview of graph theory algorithms in computer science and mathematics.
๐ฝWatch
๐ฒChannel: @ComplexNetworkAnalysis
#video #Graph #course
Udemy
Graph Theory Algorithms
A complete overview of graph theory algorithms in computer science and mathematics.
๐Graph Clustering with Graph Neural Networks
๐Publish year: 2020
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Graph #Clustering #GNN
๐Publish year: 2020
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Graph #Clustering #GNN
๐๐Network Analysis Made Simple
๐ฅNetwork Analysis Made Simple is a collection of Jupyter notebooks designed to help you get up and running with the NetworkX package in the Python programming langauge. It's written by programmers for programmers, and will give you a basic introduction to graph theory, applied network science, and advanced topics to help kickstart your learning journey. There's even case studies to help those of you for whom example narratives help a ton!
๐ฝWatch & study
๐ฒChannel: @ComplexNetworkAnalysis
#video #Graph #course #python #code #ebook
๐ฅNetwork Analysis Made Simple is a collection of Jupyter notebooks designed to help you get up and running with the NetworkX package in the Python programming langauge. It's written by programmers for programmers, and will give you a basic introduction to graph theory, applied network science, and advanced topics to help kickstart your learning journey. There's even case studies to help those of you for whom example narratives help a ton!
๐ฝWatch & study
๐ฒChannel: @ComplexNetworkAnalysis
#video #Graph #course #python #code #ebook
๐Curriculum Graph Machine Learning: A Survey
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Survey #Machine_Learning #Graph
๐Publish year: 2023
๐Study paper
๐ฒChannel: @ComplexNetworkAnalysis
#paper #Survey #Machine_Learning #Graph
๐Relative, local and global dimension in complex networks
๐Journal: NATURE COMMUNICATIONS (I.F=17.694)
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Relative #local #global #dimension
๐Journal: NATURE COMMUNICATIONS (I.F=17.694)
๐Publish year: 2022
๐Study paper
๐ฑChannel: @ComplexNetworkAnalysis
#paper #Relative #local #global #dimension