Graph Theory Algorithm is implemented in python. Jupyter Notebook is used to demonstrate the concept and Networkx library is used in several algorithms to visualize the graph.

This repository presents a comprehensive exploration of stochastic network models, focusing on the generation of random graphs and the analysis of random walks on these networks. The project aims to ...

Graph limit theory provides a rigorous framework for analysing sequences of large graphs by representing them as continuous objects known as graphons – symmetric measurable functions on the unit ...

Abstract: Graphs are highly flexible data structures that can model various data and relationships. By using graphs, we can abstract and represent various things in the real world. The technology of ...

Abstract: Distributed graph filters can be implemented over wireless sensor networks by means of cooperation and exchanges among nodes. However, in practice, the performance of such graph filters is ...

Applying the exponential random graph model (Robins et al. 2007) to the investment data of Japanese venture capital (VC) firms, we document the relationship between VC performance and the dynamics of ...

Just as Pinterest has become increasingly important to marketers, it’s been said that the first company to own sentiment, or the interest graph, in a social context will be a force to be reckoned with ...