cumbof/hdlib
Hyperdimensional Computing Library for building Vector-Symbolic Architectures in Python 3
This library helps researchers and scientists design and implement Vector-Symbolic Architectures (VSA), also known as Hyperdimensional Computing. It takes high-dimensional data inputs and processes them by combining vectors to represent information, which can then be used for tasks like classification, regression, and clustering. This is useful for those working in AI, cognitive science, bioinformatics, and other scientific disciplines looking for a novel computing approach.
Available on PyPI.
Use this if you are a researcher or scientist exploring advanced computing paradigms like Hyperdimensional Computing for problems in artificial intelligence, cognitive science, or various scientific domains.
Not ideal if you are looking for a traditional machine learning library with pre-built models and less emphasis on the underlying architectural design.
Stars
28
Forks
3
Language
Python
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Dependencies
3
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