luigibonati/mlcolvar
A unified framework for machine learning collective variables for enhanced sampling simulations
This project helps computational chemists and molecular scientists design and test machine learning-based 'collective variables' for enhanced sampling simulations. You provide simulation data, and it helps you identify critical reaction coordinates, making your molecular simulations more efficient. It's built for researchers working on molecular dynamics and related simulations.
134 stars. Available on PyPI.
Use this if you need to identify and utilize effective collective variables to accelerate your molecular dynamics simulations and explore rare events more efficiently.
Not ideal if you are not working with enhanced sampling molecular simulations or do not need to derive data-driven collective variables.
Stars
134
Forks
36
Language
Python
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Dependencies
9
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