Temporal Network Noise Contrastive Estimation (teneNCE) for Dynamic Link Prediction
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Updated
Aug 31, 2024 - Python
Temporal Network Noise Contrastive Estimation (teneNCE) for Dynamic Link Prediction
Python package for importing and analyzing discrete- and continuous-time dynamic networks
Booklet and exam of Artificial Intelligence Master Degree at Amirkabir University of technology.
Framework for calculating the steady-state energy flow and for solving optimization problems in coupled energy grids (gas, heat, electricity)
Tool to numerically solve and analyse simplicial Kuramoto models.
Implementation of Complex Networks Algorithms
Julia and Python complex system applications in ecology, epidemiology, sociology, economics & finance; network science models including Bianconi-Barabási, Barabási-Albert, Watts-Strogatz, Waxman Model & Erdős-Rényi; graph theory algorithms involving Gillespie, Bron Kerbosch, Ramsey, Bellman Ford, A*, Kruskal, Borůvka, Prim, Dijkstra, DSatur, Ran…
This is the source code of paper "Heterogeneous networks structure reconstruction via compressive sensing and clustering",DOI: 10.1109/TETCI.2020.2997011
Simulation of the COVID pandemic on the bilayer network and study the influence of social media on behaviors of individuals.
We present AFIF, Automatically Finding Important Features, an efficient solution to examine communities' structural features and also to find a proper subset of promising features in order to predict the upcoming changes of social networks.
Place to hide my stuff of Complex Network Analysis
A complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in graphs modelling of real systems.
Twitter and Influence
Mapping Science
This is a simple school assignment. I just have to implement an algorithm to calculate betweenness centrality.
This generates the complex network from a set of GPX trajectories. It is the implementation of https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177712
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