HoloVec Examples

Demonstrations and tutorials for hyperdimensional computing with HoloVec

This directory contains comprehensive, well-documented examples covering everything from 5-minute quickstarts to advanced theoretical validation. All examples are designed to be intuitive, executable, and suitable for integration into tutorials and documentation.

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Quick Start

New to HoloVec? Start here with these foundational examples:

• 00_quickstart.py - Get started in 5 minutes

• 01_basic_operations.py - Understand core VSA operations

• 02_models_comparison.py - Learn when to use each model

Learning Paths

Path 1: Absolute Beginner

Time: ~30 minutes

1. 00_quickstart.py - Get started in 5 minutes

2. 01_basic_operations.py - Understand core VSA operations

3. 02_models_comparison.py - Learn when to use each model

4. 10_encoders_scalar.py - Encode continuous values

5. 13_encoders_position_binding.py - Encode sequences

Path 2: Application Developer

Time: ~1-2 hours

1. Start with Path 1 basics

2. Choose your domain:

   • Text/NLP: 14_encoders_ngram.py → 20_app_text_classification.py

   • Images: 17_encoders_image.py → 21_app_image_recognition.py

   • Sequences: 15_encoders_trajectory.py → 22_app_gesture_recognition.py

Path 3: Researcher / Advanced User

Time: ~2-3 hours

1. Complete Path 1 and 2

2. Explore advanced topics:

   • Theory: 30_theory_fpe_validation.py, 32_distributed_representations.py

   • Performance: 31_performance_benchmarks.py

   • Memory: 27_cleanup_strategies.py, 28_factorization_methods.py

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Browse All Examples

Below you’ll find all available examples organized by category.

HoloVec Quickstart Guide

HoloVec Quickstart Guide

Demo: Basic VSA Operations

Demo: Basic VSA Operations

VSA Models Comparison Guide

VSA Models Comparison Guide

Comprehensive demo of scalar encoders in holovec.

Comprehensive demo of scalar encoders in holovec.

Fractional Power Encoder Deep Dive

Fractional Power Encoder Deep Dive

Thermometer and Level Encoders Deep Dive

Thermometer and Level Encoders Deep Dive

Position-Based Sequence Encoding

Position-Based Sequence Encoding

Demonstration of N-gram Encoder for local sequence pattern encoding.

Demonstration of N-gram Encoder for local sequence pattern encoding.

Demonstration of Trajectory Encoder for continuous sequence encoding.

Demonstration of Trajectory Encoder for continuous sequence encoding.

Multivariate Vector Encoding

Multivariate Vector Encoding

Demonstration of Image Encoder for 2D spatial data encoding.

Demonstration of Image Encoder for 2D spatial data encoding.

Compositional Graph Encoding

Compositional Graph Encoding

Document Classification with N-grams

Document Classification with N-grams

Image Pattern Recognition

Image Pattern Recognition

Gesture Recognition from Motion Trajectories

Gesture Recognition from Motion Trajectories

Symbolic Reasoning with Role-Filler Binding

Symbolic Reasoning with Role-Filler Binding

Working Memory with Cleanup Strategies

Working Memory with Cleanup Strategies

Integration Patterns and Multimodal Fusion

Integration Patterns and Multimodal Fusion

Retrieval demo using ItemStore + Codebook

Retrieval demo using ItemStore + Codebook

Cleanup Strategies Comparison

Cleanup Strategies Comparison

Multi-Factor Unbinding and Factorization Methods

Multi-Factor Unbinding and Factorization Methods

Validate FractionalPowerEncoder against theoretical predictions from Frady et al. (2021).

Validate FractionalPowerEncoder against theoretical predictions from Frady et al. (2021).

Performance Benchmarks

Performance Benchmarks

Distributed Representations and Capacity Analysis

Distributed Representations and Capacity Analysis

Error Handling and Robustness

Error Handling and Robustness

HRR correlation vs convolution demo

HRR correlation vs convolution demo

GHRR usage example: diagonality/m sweeps and non-commutativity trends

GHRR usage example: diagonality/m sweeps and non-commutativity trends

BSDC-SEG demo: segment-sparse codes, bundling, and segment-wise search

BSDC-SEG demo: segment-sparse codes, bundling, and segment-wise search