weighted-graphs

[ACM Computing Surveys'23] Implementations or refactor of some temporal link prediction/dynamic link prediction methods and summary of related open resources for survey paper "Temporal Link Prediction: A Unified Framework, Taxonomy, and Review" which has been accepted by ACM Computing Surveys.

Dart implementation of a directed graphs and graph crawler. Provides algorithms for sorting vertices, retrieving a topological ordering and detecting cycles.

Simple weighted graphs. Requires LightGraphs.jl.

A set of efficient data structures in C, created in a generic way

Weighted and unweighted graphs and digraphs with C++

A LightGraphs.jl compatible graph package for graphs with multiple vertex, edge and graph metadata.

Python package for the visualization of food webs (trophic networks)

PathQuick is a high-performance software solution designed to calculate the quickest path between two landmarks in the United States.

The aim of this project is to create a program capable of generating a maze and then solving it by identifying the shortest path between the entrance and the exit.

[TKDE'23] Demo code of the paper entitled "High-Quality Temporal Link Prediction for Weighted Dynamic Graphs via Inductive Embedding Aggregation", which has been accepted by IEEE TKDE

Node embedding for directed, weighted networks

gene-set clustering and network visualization

The Floyd–Warshall algorithm finds the shortest paths (and distances) in a directed weighted graph

Minimal Cycle Basis calculation for Weighted Undirected Graphs (greedy approach)

A tool to make weighted radar charts.

Extended Modularity (EQ) for communities in Python

Ant colony optimization algorithm simulation with visualization.

Weighted Directed Graphs - Assignment

Two models of epidemic spreading in weighted networks using Julia.

A Java-based project that visualizes a traffic management system using graph structures and JavaFX. It demonstrates node and edge representation for traffic flow between locations, providing an interactive and visual approach to understanding connectivity.