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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
Comparing features of the Erdos-Renyi graph with a Real-world graph (MT) with the same number of nodes!
Review of different models for generating 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.
Simulation of various complex networks.
Реализация программы-калькулятора для вычисления характеристик случайных графов // Implementation of program for calculating characteristics of random graphs
Code to study the different parameters for random network models including degree distribution, clustering coeffecient and path length. Part of CSEN 354: Social Networks Analysis & Risks taught by Dr. Xiang Li at Santa Clara University.
Contains GCN training and a module that generates Erdos Reyni Graphs for training.
Modified gap statistic (gap-com) for regularization selection of sparse networks. This method is aimed for complex network estimation.
The code and results for finding anchor nodes in different networks which reduce the APL of the network.