GitHub

A utility that efficiently calculates Closeness, Node Betweenness and Edge Betweenness of a given connected, undirected graph.

The implementation is based on [1] and was extended to simultaneously calculate Closeness and Edge Betweenness metrics as well. Time complexity is O(nm) for non-weighted and O((nm + n^2)logn) for ...
marktechpost

CMU and Google Researchers Open-Source ‘python_graphs’, a Library for Representing Python Programs as Graphs for Machine Learning Research

Graphs are the ultimate tools of storytelling for Data scientists and engineers, but there exists another type of graph called code graphs. These graphs are the visual representation of the code and ...
01Net

BlackSwan Technologies Wins Most Innovative Knowledge Graph Implementation at A-Team Innovation Awards 2022

LONDON–(BUSINESS WIRE)–#ai–Cloud enterprise software leader BlackSwan Technologies has won the category for the Most Innovative Implementation of Knowledge Graph Technologies at the 2022 A-Team ...
GitHub

Modeling real world social network interactivity using unweighted undirected graphs.

This project uses an adjacency matrix (like the one below) to represent the vertices and edges in the network. Each node in the graph is a unique user that can be linked to other users through the ...
IEEE

A Probabilistic Algorithm to Estimate the Spectral Moments of Large Undirected Weighted Graphs

Abstract: Complex networks are often used to model real systems. Examples of such networks include computer networks, cities in a state or countries interconnected by highways, the connection between ...
IEEE

Probabilistic Undirected Graph Based Denoising Method for Dynamic Vision Sensor

Abstract: Dynamic Vision Sensor (DVS) is a new type of neuromorphic event-based sensor, which has an innate advantage in capturing fast-moving objects. Due to the interference of DVS hardware itself ...