Torchhd is a Python library for Hyperdimensional Computing and Vector Symbolic Architectures
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Updated
Jun 19, 2025 - Python
Torchhd is a Python library for Hyperdimensional Computing and Vector Symbolic Architectures
The Fuzzy-Pattern Tsetlin Machine library, with zero external dependencies, performs blazingly fast.
Cognitive Computing with Associative Memory
Accelerator for Hyperdimensional Computing (HDC)
Hyperdimensional Computing Library for building Vector-Symbolic Architectures in Python 3
Hyperdimensional computing in JAX, with statistical guarantees.
Boolean Hypervectors with various operators for experiments in hyperdimensional computing (HDC).
An automated HDC platform
A collection of Hyperdimensional Computing (HDC) models implemented in C++
A Rust library for hyperdimensional computing (HDC)
HDC-X: A Hyperdimensional Computing Framework for Efficient Classification on Low-Power Devices
A chef's palate for AI agent memory; Un-mix any day's work into its exact projects, and detect workstreams nobody has named yet. Hyperdimensional fingerprints, zero dependencies.
A library for training and running HDC models on embedded devices.
Holographic vectors you can compute with. Bind structure, bundle sets, unbind components cross NumPy, PyTorch, and JAX.
A computational foundation for AGI based on hyperdimensional computing and set theory.
A cognitive substrate for AI agents — hyperdimensional memory with first-class goals, beliefs, sensory, self-model, and a non-destructive unlearn primitive. Rust top to bottom, embedded-first, no LLM in the read path. One binary, no query language.
A high-performance autonomous bitwise model leveraging Vector Symbolic Architectures (VSA) and Hyperdimensional Computing (HDC). Built in Rust.
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