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

Repository made for didactic purposes. We reproduce some of the results of the research article: "Albert, R., Jeong, H. & Barabási, AL. Error and attack tolerance of complex networks. Nature 406, 378–382 (2000). https://doi.org/10.1038/35019019".

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.