no code implementations • 27 Jan 2022 • 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 operates with distributed vector representations of large fixed dimensionality.
no code implementations • 31 Dec 2021 • Dmitri A. Rachkovskij
However, they can be adapted to hypervectors in formats of other HDC/VSA models, as well as for representing sequences of types other than symbolic strings.
no code implementations • 12 Nov 2021 • Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov, Abbas Rahimi
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 Architectures (HDC/VSA).
no code implementations • 11 Nov 2021 • Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov, Abbas Rahimi
Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations.
no code implementations • 9 Jun 2021 • Denis Kleyko, Mike Davies, E. Paxon Frady, Pentti Kanerva, Spencer J. Kent, Bruno A. Olshausen, Evgeny Osipov, Jan M. Rabaey, Dmitri A. Rachkovskij, Abbas Rahimi, Friedrich T. Sommer
We see them acting as a framework for computing with distributed representations that can play a role of an abstraction layer for emerging computing hardware.