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 with statistical guarantees: calibrated probabilities, conformal prediction sets, anomaly detection with a guaranteed false-positive rate
Hyperdimensional Computing Library for building Vector-Symbolic Architectures in Python 3
GPU-accelerated neural network operations using Vulkan compute shaders.
Nazgul is a unified C++/Python framework for time-optimal multi-joint trajectory planning (inherited from LongTermPlanner) and edge-efficient hyperdimensional computing (imported from Arthedain), providing a VSA backend factory with 8 algebras, HDC energy analysis at 45nm CMOS
FPGA-accelerated event-based normal flow estimation and real-time collision avoidance for drones — 100Hz end-to-end with microsecond latency.
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.
Repository for HYPERDOA: Robust and Efficient DoA Estimation using Hyperdimensional Computing
"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
Hyperprobe is the Python implementation of the framework proposed in the paper "Hyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures".
Keynote presentation for the Midnight Sun Workshop on Vector Symbolic Architectures
Composition-episodic cognitive memory for AI agents (VSA + lattice geometry)
This project aims to develop a very basic Vector Symbolic Architecture model to use as a default model in my other VSA projects.
A quantum Hyper-Dimensional Computing (qHDC) framework in Qiskit.
Cognitive engine based on Hyperdimensional Computing (HDC) and Vector Symbolic Architectures (VSA) for deterministic reasoning in B^100,000 space.
Deterministic logical reasoning engine using Vector Symbolic Architectures. 100% ProofWriter. CPU-only. No backprop.
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
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