Implementation and application of graph theory, social network mining, reinforcement learning, and inverse reinforcement learning.

Complex networks such as ER, BA networks and many more :)

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.

This project is a visualization of the network science models. Uses CytoScape.js to visualize the models.

Models of Bak-Tang-Wiesenfeld, Manna, Feders and stochastic Feders sand piles on cellular automaton and random graphs in Python 3

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.