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
Cognitive Computing with Associative Memory
Hyperdimensional Computing Library for building Vector-Symbolic Architectures in Python 3
"VSA, Analogy, and Dynamic Similarity" presentation given at the Workshop on Developments in Hyperdimensional Computing and Vector Symbolic Architectures, Heidelberg, Germany, 2020-03-16.
Publications by Peter Overmann
[code] Behavioral Time Scale Synaptic Plasticity (BTSP) endows Hyperdimensional Computing with brain-like information retrieval flexibility
Hyperprobe is the Python implementation of the framework proposed in the paper "Hyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures".
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.
Keynote presentation for the Midnight Sun Workshop on Vector Symbolic Architectures
A quantum Hyper-Dimensional Computing (qHDC) framework in Qiskit.
Source code of the slides for the lecture "Analogical Reasoning" given on 2021-10-06 as Module 6 of Neuroscience 299: Computing with High-Dimensional Vectors at the Redwood Center for Theoretical Neuroscience, University of California, Berkeley
Research to use Vector Symbolic Architectures to implement altitude hold in a simulated multicopter.
HDSC: classifying pulmonary fibrosis extensions harnessing lung ultrasound spectroscopy and HDC/VSA analysis
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