aleCombi/ChenSignatures.jl

A high-performance Julia library for computing path signatures, log-signatures (Lyndon basis), and free tensor algebra operations.

25
/ 100
Experimental

This tool helps researchers and practitioners analyze complex time-series data, like financial market movements or sensor readings, by transforming them into 'path signatures' or 'log-signatures'. These outputs simplify the underlying geometric structure of the data. It's designed for quantitative analysts, machine learning engineers working with sequential data, and mathematicians in stochastic analysis who need a robust way to represent and compare paths.

Use this if you need to extract robust, coordinate-free features from path-like data for tasks such as prediction, classification, or understanding complex time-evolving systems.

Not ideal if you are only working with simple, low-dimensional time series that don't require advanced geometric feature extraction or if you prefer a different mathematical representation of paths.

financial-time-series stochastic-analysis machine-learning-features quantitative-finance data-stream-analysis
No Package No Dependents
Maintenance 6 / 25
Adoption 4 / 25
Maturity 15 / 25
Community 0 / 25

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7

Forks

Language

Julia

License

MIT

Last pushed

Jan 04, 2026

Commits (30d)

0

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