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Post #832 1.45K
🎞 Network Theory

💥Free recorded course.

💥This lecture will discuss Network Theory:
Part I – Static networks:
🔸Understand the notion of networks as graphs consisting of nodes and edges:
-Directed vs undirected
-Weighted unweighted
🔸Understand different topologies and how they affect the network:
-Random
-Preferential
🔸Know the meaning of the basic network metrics:
-Graph diameter
-Shortest Average Path Length
-Degree distributions
-Minimum spanning tree
🔸Understand basic network evolution processes:
-Small world networks

Part II – Dynamic networks
Network visualization:
-Why network views are important
-Graph layouts
🔸Networks vs hierarchies
Using networks:
-Inuput/Output analysis
-LCA
🔸Measuring real networks:
-Economies
-Wikis/knowledge
-Ecosystems
🔸Processes on networks:
-Avalanche models
-Metcalfe’s law

📽 Watch

📲Channel: @ComplexNetworkAnalysis

#video #course #network #Graph
TU Delft OCW Network Theory - TU Delft OCW
  • 👍 3
Post #831 566
📄 Review on Learning and Extracting Graph Features for Link Prediction

📘journal: MACHINE LEARNING AND KNOWLEDGE EXTRACTION
🗓Publish year: 2020

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Learning #Extracting #Graph #Features #Link_Prediction #review
  • 👍 1
Post #830 567
🎞 Network Analysis of Organizations

💥Free recorded course by professor Daniel A. McFarland.

💥In this course, we will describe how organization’s researchers look at social networks within organizations. In addition, we will describe how some theorists contend there is a network form of organization that is distinct from hierarchical organizations and markets. So we will relate two perspectives: a purely analytic one that describes networks within organizations, and a theoretical one concerning a prescribed form of inter- organizational association that can result in better outputs.

📽 Watch

📲Channel: @ComplexNetworkAnalysis

#video #course #network
  • 👏 2
Post #829 512
📑Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems

🗓Publish year: 2023

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #machine_learning #Application
  • 👍 4
Post #828 560
📄 Community detection for multilayer weighted networks

📘journal: Information Sciences(I.F=8.233)
🗓Publish year: 2022

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Community_detection #multilayer #weighted_networks
  • 👍 2
Post #827 522
📑Considering weights in real social networks: A review

📘journal: Frontiers in Physics(I.F=3.718)
🗓Publish year: 2023

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #social_networks #Review
  • 👍 2
  • 👏 1
Post #826 553
📄 A survey of community detection methods in multilayer networks

📘journal: Data Mining and Knowledge Discovery (I.F=5.406)
🗓Publish year: 2021

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #community_detection #methods #multilayer #survey
  • 👍 1
Post #825 511
📑A Review of Graph and Network Complexity from an Algorithmic Information Perspective

📘journal: Entropy (I.F=2.738)
🗓Publish year: 2018

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Review
  • 👍 5
  • 👏 1
Post #824 506
📄 Role-Aware Information Spread in Online Social Networks

📘journal: ENTROPY-SWITZ (I.F=2.738)
🗓Publish year: 2021

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Role_Aware #Information #Spread #Online
  • 👍 1
Post #823 3.93K
📄 Precision medicine — networks to the rescue

📘journal: Current Opinion in Biotechnology (COBIOT) (I.F=10.279)
🗓Publish year: 2020

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #iPrecision #medicine #networks #rescue
  • 👍 4
Post #822 2.11K
🎞 Machine Learning with Graphs: Theory of Graph Neural Networks

💥Free recorded course by Jure Leskovec, Computer Science, PhD

💥The topics: How expensive are graph neural networks, designing the most powerful GNNs.

📽 Watch: part1 part2

📲Channel: @ComplexNetworkAnalysis

#video #course #Graph #Machine_Learning #GNN
YouTube Stanford CS224W: ML with Graphs | 2021 | Lecture 9.1 - How Expressive are Graph Neural Networks For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3GwTmur Jure Leskovec Computer Science, PhD In this lecture, we provide a theoretical framework to analyze the expressive power…
  • 👍 1
Post #820 998
📑Graph-powered learning methods in the Internet of Things: A survey

📘journal: Machine Learning with Applications (I.F=3.203)
🗓Publish year: 2023

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #IOT #Survey
  • 👍 3
Post #819 630
📑 Link Prediction on Complex Networks: An Experimental Survey

📘journal: Data Science and Engineering (I.F=4.52)
🗓Publish year: 2022

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #Survey
  • 👍 2
Post #817 583
Python for Graph and Network Analysis👇👇👇👇👇
  • 👌 3
Post #813 588
📄 20 years of network community detection

📘journal: NATURE PHYSICS(I.F=19.684)
🗓Publish year: 2022

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #years #community_detection
  • 👍 3
Post #811 565
📄From past to present: Spam detection and identifying opinion leaders in social networks

📘Journal : SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES
🗓Publish year: 2022

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #past #present #Spam_detection #identifying #opinion #leaders
  • 👍 3
  • 👏 1
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