msmbuilder/vde
Variational Autoencoder for Dimensionality Reduction of Time-Series
This tool helps scientists analyze high-dimensional time-series data from chemical and biophysical systems, such as molecular simulations. You input complex trajectory data and it outputs a simplified representation that highlights the most important dynamic features. It's designed for researchers who study how systems change over time, like protein folding or molecular interactions.
190 stars. No commits in the last 6 months.
Use this if you need to understand the underlying, often nonlinear, dynamics within complex time-series data from molecular or biophysical experiments.
Not ideal if your data dynamics are primarily linear or if you need a simple, interpretable linear model for dimensionality reduction.
Stars
190
Forks
42
Language
Jupyter Notebook
License
MIT
Last pushed
May 01, 2022
Commits (30d)
0
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