147 citations · 401 across the 7 of their papers we have counts for
8 papers
Derandomizing Dense Binary Hypervector Codebooks for Quantized Scalars
Dmitri Rachkovskij, Evgeny Osipov, Olexander Volkov +2
Hyperdimensional computing and vector symbolic architectures often represent quantized scalar levels by dense binary codebooks whose level-to-level similarity is intended to follow…
On Design Choices in Similarity-Preserving Sparse Randomized Embeddings
Denis Kleyko, Dmitri A. Rachkovskij
Expand & Sparsify is a principle that is observed in anatomically similar neural circuits found in the mushroom body (insects) and the cerebellum (mammals). Sensory data are projec…
Recursive Binding for Similarity-Preserving Hypervector Representations of Sequences
Dmitri A. Rachkovskij, Denis Kleyko
Hyperdimensional computing (HDC), also known as vector symbolic architectures (VSA), is a computing framework used within artificial intelligence and cognitive computing that opera…
Shift-Equivariant Similarity-Preserving Hypervector Representations of Sequences
Dmitri A. Rachkovskij
Hyperdimensional Computing (HDC), also known as Vector-Symbolic Architectures (VSA), is a promising framework for the development of cognitive architectures and artificial intellig…
A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges
Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov +1
This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectur…
A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations
Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov +1
This two-part comprehensive survey is devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). B…
Vector Symbolic Architectures as a Computing Framework for Emerging Hardware
Denis Kleyko, Mike Davies, E. Paxon Frady +8
This article reviews recent progress in the development of the computing framework vector symbolic architectures (VSA) (also known as hyperdimensional computing). This framework is…
Neural Distributed Autoassociative Memories: A Survey
V. I. Gritsenko, D. A. Rachkovskij, A. A. Frolov +3
Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vecto…