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A Theoretical Perspective on Hyperdimensional Computing

arXiv 2010.07426 ↗First posted 14 Oct 2020cs.LGcited by 43

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Abstract (arXiv)

Hyperdimensional (HD) computing is a set of neurally inspired methods for obtaining high-dimensional, low-precision, distributed representations of data. These representations can be combined with simple, neurally plausible algorithms to effect a variety of information processing tasks. HD computing has recently garnered significant interest from the computer hardware community as an energy-efficient, low-latency, and noise-robust tool for solving learning problems. In this review, we present a unified treatment of the theoretical foundations of HD computing with a focus on the suitability of representations for learning.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Oct 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 7; 2024: 12; 2025: 9; 2026: 9.

43 papers.

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  1. 2021A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformationscited by 99
  2. 2021Vector Symbolic Architectures as a Computing Framework for Emerging Hardwarecited by 35
  3. 2024Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6Gcited by 31
  4. 2022LeHDC: Learning-Based Hyperdimensional Computing Classifiercited by 17
  5. 2023Learning from Hypervectors: A Survey on Hypervector Encodingcited by 7
  6. 2024Generalized Holographic Reduced Representationscited by 6
  7. 2025Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perceptioncited by 6
  8. 2024Hyperdimensional Representation Learning for Node Classification and Link Predictioncited by 5
  9. 2024Lifelong Intelligence Beyond the Edge using Hyperdimensional Computingcited by 5
  10. 2022An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computingcited by 4
  11. 2024Laplace-HDC: Understanding the geometry of binary hyperdimensional computingcited by 4
  12. 2022Streaming Encoding Algorithms for Scalable Hyperdimensional Computingcited by 3
31 more
  1. 2023Capacity Analysis of Vector Symbolic Architecturescited by 3
  2. 2023Efficient Model Adaptation for Continual Learning at the Edgecited by 3
  3. 2024MicroHD: An Accuracy-Driven Optimization of Hyperdimensional Computing Algorithms for TinyML systemscited by 3
  4. 2024Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networkscited by 3
  5. 2024Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardwarecited by 3
  6. 2022Graph Embeddings via Tensor Products and Approximately Orthonormal Codescited by 2
  7. 2023Hyperdimensional Computing as a Rescue for Efficient Privacy-Preserving Machine Learning-as-a-Servicecited by 2
  8. 2023The Hyperdimensional Transform for Distributional Modelling, Regression and Classificationcited by 2
  9. 2024Hyperdimensional computing: a fast, robust and interpretable paradigm for biological datacited by 2
  10. 2024Self-Attention Based Semantic Decomposition in Vector Symbolic Architecturescited by 2
  11. 2025DPQ-HD: Post-Training Compression for Ultra-Low Power Hyperdimensional Computingcited by 2
  12. 2025Linearithmic Clean-up for Vector-Symbolic Key-Value Memory with Kroneker Rotation Productscited by 2
  13. 2026Bridging the Gap Between Hyperdimensional Computing and Kernel Methods via the Nystr"om Methodcited by 2
  14. 2024Enhanced Detection of Transdermal Alcohol Levels Using Hyperdimensional Computing on Embedded Devicescited by 1
  15. 2024On Design Choices in Similarity-Preserving Sparse Randomized Embeddingscited by 1
  16. 2025MEMHD: Memory-Efficient Multi-Centroid Hyperdimensional Computing for Fully-Utilized In-Memory Computing Architecturescited by 1
  17. 2026Large-Margin Hyperdimensional Computing: A Learning-Theoretical Perspectivecited by 1
  18. 2023HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representationscited by 0
  19. 2023A Framework for Analyzing Cross-correlators using Price's Theorem and Piecewise-Linear Decompositioncited by 0
  20. 2025High-resolution spatial memory requires grid-cell-like neural codescited by 0
  21. 2025FedUHD: Unsupervised Federated Learning using In-Memory Hyperdimensional Computingcited by 0
  22. 2025MissionHD: Hyperdimensional Refinement of Distribution-Deficient Reasoning Graphs for Video Anomaly Detectioncited by 0
  23. 2025EP-HDC: Hyperdimensional Computing with Encrypted Parameters for High-Throughput Privacy-Preserving Inferencecited by 0
  24. 2025Efficient Vector Symbolic Architectures from Histogram Recoverycited by 0
  25. 2026Hyperdimensional Cross-Modal Alignment of Frozen Language and Image Models for Efficient Image Captioningcited by 0
  26. 2026Holographic Invariant Storage: Design-Time Safety Contracts via Vector Symbolic Architecturescited by 0
  27. 2026HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computingcited by 0
  28. 2026Graph-Structured Hyperdimensional Computing for Data-Efficient and Explainable Process-Structure-Property Predictioncited by 0
  29. 2026Hyperdimensional computing for structured querying on tabular data embeddingscited by 0
  30. 2026Vector Symbolic Policy Gradientcited by 0
  31. 2026High-probability guarantees for linear accessibility in feature superpositioncited by 0