📄Complex Network Analysis of China National Standards for New Energy Vehicles
📘Journal: Sustainability(I.F=3.889)
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
📘Journal: Sustainability(I.F=3.889)
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
👨💻 MSc position at SBNA (Social & Biological Network Analysis) Lab
🇮🇷 Language: IR
🌐 Details
📲Channel: @ComplexNetworkAnalysis
🇮🇷 Language: IR
🌐 Details
📲Channel: @ComplexNetworkAnalysis
📄A Mini review of Node Centrality Metrics in Biological Networks
📘Journal: International Journal of Network Dynamics and Intelligence
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #centrality #biological
📘Journal: International Journal of Network Dynamics and Intelligence
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #centrality #biological
👍3
🎞 Knowledge Graph Seminar Session 1 (Spring 2020)
💥Free recorded tutorial on Knowledge Graph.
📽Watch
📱Channel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
💥Free recorded tutorial on Knowledge Graph.
📽Watch
📱Channel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
YouTube
CS520: Knowledge Graph Seminar Session 1 (Spring 2020)
What is a Knowledge Graph?
📄A Network Science perspective of Graph Convolutional Networks: A survey
📘Journal: FUTURE INTERNET
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #perspective #Convolutional #survey
📘Journal: FUTURE INTERNET
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #perspective #Convolutional #survey
📄Network Analysis of Road Traffic Crash and Rescue Operations in Federal Capital City
📘Journal: International Journal of Geosciences (I.F=1.525)
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Traffic
📘Journal: International Journal of Geosciences (I.F=1.525)
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Traffic
📄Graph-based Time-Series Anomaly Detection: A Survey
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Time_Series #Anomaly #survey
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Time_Series #Anomaly #survey
📄Women financial inclusion research: a bibliometric and network analysis
📘Journal: INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Women #financial #inclusion #bibliometric
📘Journal: INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Women #financial #inclusion #bibliometric
📄Predicting the establishment and removal of global trade relations for import and export of petrochemical products
📘Journal: Energy (I.F=8.857)
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #prediction #trade #petrochemical
📘Journal: Energy (I.F=8.857)
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #prediction #trade #petrochemical
🎞 Graph Theory Algorithms
💥A complete overview of graph theory algorithms in computer science and mathematics.
📽Watch
📲Channel: @ComplexNetworkAnalysis
#video #Graph #course
💥A complete overview of graph theory algorithms in computer science and mathematics.
📽Watch
📲Channel: @ComplexNetworkAnalysis
#video #Graph #course
Udemy
Graph Theory Algorithms
A complete overview of graph theory algorithms in computer science and mathematics.
📄Graph Clustering with Graph Neural Networks
🗓Publish year: 2020
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Clustering #GNN
🗓Publish year: 2020
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Clustering #GNN
👍4
🎞📙Network Analysis Made Simple
💥Network 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!
📽Watch & study
📲Channel: @ComplexNetworkAnalysis
#video #Graph #course #python #code #ebook
💥Network 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!
📽Watch & study
📲Channel: @ComplexNetworkAnalysis
#video #Graph #course #python #code #ebook
👍4
📄Curriculum Graph Machine Learning: A Survey
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Survey #Machine_Learning #Graph
🗓Publish year: 2023
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Survey #Machine_Learning #Graph
👍2
📄Relative, local and global dimension in complex networks
📘Journal: NATURE COMMUNICATIONS (I.F=17.694)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Relative #local #global #dimension
📘Journal: NATURE COMMUNICATIONS (I.F=17.694)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Relative #local #global #dimension
📄Graph Algorithms with Python
💥Technical paper
📝In this paper, the auther will take you through the implementation of Graph Algorithms with Python. As a data scientist, you should be well aware to find relationships among people by using the network they create within each other. So here the auther will take you through the Graph Algorithms you should know for Data Science using Python.
🌐 Study
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #python #code
💥Technical paper
📝In this paper, the auther will take you through the implementation of Graph Algorithms with Python. As a data scientist, you should be well aware to find relationships among people by using the network they create within each other. So here the auther will take you through the Graph Algorithms you should know for Data Science using Python.
🌐 Study
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #python #code
thecleverprogrammer
Graph Algorithms with Python | Aman Kharwal
In this article, I will take you through the implementation of Graph Algorithms with Python. As a data scientist, you should be well aware
👍7
🎞 Knowledge Graph Seminar Session 2 (Spring 2020)
💥Free recorded tutorial on Knowledge Graph.
📽Watch
📱Channel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
💥Free recorded tutorial on Knowledge Graph.
📽Watch
📱Channel: @ComplexNetworkAnalysis
#video #Knowledge_Graph #seminar
YouTube
CS 520: Knowledge Graph Seminar Session 2 (Spring 2020)
How to Create a Knowledge Graph?
👍5
📄A Mini Review of Node Centrality Metrics in Biological Networks
📘Journal: International Journal of Network Dynamics and Intelligence
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #node_centrality #biological_network
📘Journal: International Journal of Network Dynamics and Intelligence
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #node_centrality #biological_network
❤3👍1👏1
📄A social network analysis of two networks: Adolescent school network and Bitcoin trader network
📘Journal: Decision Analytics Journal
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Adolescent #school #Bitcoin #trader
📘Journal: Decision Analytics Journal
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Adolescent #school #Bitcoin #trader
👍3
2017_Knowledge_Graph_Embedding_A_Survey_of_Approaches_and_Applications.pdf
970.4 KB
📄Knowledge Graph Embedding: Survey of Approaches and Applications
📘Journal: IEEE Transactions on Knowledge and Data Engineering (I.F=9.235)
🗓Publish year: 2017
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Embedding #DeepLearning #Survey
📘Journal: IEEE Transactions on Knowledge and Data Engineering (I.F=9.235)
🗓Publish year: 2017
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Embedding #DeepLearning #Survey
👍3
🎞 Machine Learning with Graphs: Introduction to Graph Neural Networks, Basics of Deep Learning, Deep Learning for Graphs
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥Starting from this lecture:
-we introduce the exciting technique of graph neural networks, that encodes node features with multiple layers of non-linear transformations based on graph structure. Graph neural networks have shown extraordinary performance in various tasks, and could tame the complex nature of graphs.
-we give a review of deep learning concepts and techniques that are essential for understanding graph neural networks. Starting from formulating machine learning as optimization problems, we introduce the concepts of objective function, gradient descent, non-linearity and back propagation.
-we’ll give you an introduction of architecture of graph neural networks. One key idea covered in the lecture is that in GNNs, we’re generating node embeddings based on local network neighborhood. Instead of single layer, GNNs usually consist of arbitrary number of layers to integrate information from even larger contexts. We then introduce how we use GNNs to solve the optimization problems, and its powerful inductive capacity.
📽 Watch: part1 part2 part3
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥Starting from this lecture:
-we introduce the exciting technique of graph neural networks, that encodes node features with multiple layers of non-linear transformations based on graph structure. Graph neural networks have shown extraordinary performance in various tasks, and could tame the complex nature of graphs.
-we give a review of deep learning concepts and techniques that are essential for understanding graph neural networks. Starting from formulating machine learning as optimization problems, we introduce the concepts of objective function, gradient descent, non-linearity and back propagation.
-we’ll give you an introduction of architecture of graph neural networks. One key idea covered in the lecture is that in GNNs, we’re generating node embeddings based on local network neighborhood. Instead of single layer, GNNs usually consist of arbitrary number of layers to integrate information from even larger contexts. We then introduce how we use GNNs to solve the optimization problems, and its powerful inductive capacity.
📽 Watch: part1 part2 part3
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
YouTube
Stanford CS224W: ML with Graphs | 2021 | Lecture 6.1 - Introduction to Graph Neural Networks
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3nvFQi3
Jure Leskovec
Computer Science, PhD
Previously we talked about some node embedding techniques that could learn task-independent…
Jure Leskovec
Computer Science, PhD
Previously we talked about some node embedding techniques that could learn task-independent…
❤5👍2🔥1🤔1