Simple projects to understand concepts from the Complex Network course at UOC: Structural Descriptors, Models of Complex Networks, Community Detection, Dynamics in CN (Epidemic simulation)
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Updated
Mar 5, 2023 - Jupyter Notebook
Simple projects to understand concepts from the Complex Network course at UOC: Structural Descriptors, Models of Complex Networks, Community Detection, Dynamics in CN (Epidemic simulation)
Альтернативный экзамен :: Реализация программы-калькулятора для вычисления характеристик случайных графов / Alternative exam :: Implementation of program for calculating characteristics of random graphs
This repository is adapt from the course materials for Honors Engineering Analysis at Northwestern University. The course is designed for Engineering first-year undergraduate students to learn about linear algebra and its applications.
Simulation of various complex networks.
Comparing features of the Erdos-Renyi graph with a Real-world graph (MT) with the same number of nodes!
Sample the G(n, m)-model of Erdős–Rényi random graphs.
Started as a numerical task to prove convergence of number of triangles in ER graph, this project grown to consist of various random graph models' implementations, such as Erdos-Renyi random graph, Generalized random graph, Configuration Model.
Review of different models for generating graphs.
Modified gap statistic (gap-com) for regularization selection of sparse networks. This method is aimed for complex network estimation.
Contains GCN training and a module that generates Erdos Reyni Graphs for training.
The code and results for finding anchor nodes in different networks which reduce the APL of the network.
Реализация программы-калькулятора для вычисления характеристик случайных графов // Implementation of program for calculating characteristics of random graphs
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