Torchhd is a Python library for Hyperdimensional Computing and Vector Symbolic Architectures

Cognitive Computing with Associative Memory

Accelerator for Hyperdimensional Computing (HDC)

Boolean Hypervectors with various operators for experiments in hyperdimensional computing (HDC).

Hyperdimensional Computing Library for building Vector-Symbolic Architectures in Python 3

An automated HDC platform

A collection of Hyperdimensional Computing (HDC) models implemented in C++

A library for training and running HDC models on embedded devices.

HDC-X: A Hyperdimensional Computing Framework for Efficient Classification on Low-Power Devices

Sub-linear knowledge retrieval via quantum-inspired hyperdimensional folded space (0.88ms @ 100% accuracy)

Contributions to my area of research as a research assistant at ULL in Hyperdimensional Computing (HDC)

"VSA, Analogy, and Dynamic Similarity" presentation given at the Workshop on Developments in Hyperdimensional Computing and Vector Symbolic Architectures, Heidelberg, Germany, 2020-03-16.

[code] Behavioral Time Scale Synaptic Plasticity (BTSP) endows Hyperdimensional Computing with brain-like information retrieval flexibility

An extended note on using Vector Symbolic Architectures to implement Next Generation Reservoir Computing

LLY-HDC uses hyperdimesnional computing and neurosymbolic AI to implement a high-performance AI model on quantum computers

A Rust library for hyperdimensional computing (HDC)

Publications by Peter Overmann

This project aims to develop a very basic Vector Symbolic Architecture model to use as a default model in my other VSA projects.

Holographic vectors you can compute with. Bind structure, bundle sets, unbind components cross NumPy, PyTorch, and JAX.