telmomenezes/synthetic
Symbolic Generators for Complex Networks
This tool helps researchers and scientists understand how complex networks, such as social networks, biological systems, or technological infrastructures, form and evolve. It takes real-world network data and automatically discovers simple computer programs that describe how these networks grow. The output is a set of 'generator' programs that can explain observed network structures and predict future growth patterns.
No commits in the last 6 months.
Use this if you need to find underlying generative rules for the growth of complex networks from observed data, rather than just describing their current state.
Not ideal if you are looking for a tool to simply visualize networks, perform static network analysis, or predict specific future node connections without inferring growth mechanisms.
Stars
47
Forks
9
Language
Python
License
MIT
Category
Last pushed
Mar 31, 2023
Commits (30d)
0
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