15 citations · 43 across the 11 of their papers we have counts for
4 papers · 1 filter
An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing
Igor Nunes, Mike Heddes, Tony Givargis +1
Hyperdimensional Computing (HDC) is a computation framework based on properties of high-dimensional random spaces. It is particularly useful for machine learning in resource-constr…
Hyperdimensional Hashing: A Robust and Efficient Dynamic Hash Table
Mike Heddes, Igor Nunes, Tony Givargis +2
Most cloud services and distributed applications rely on hashing algorithms that allow dynamic scaling of a robust and efficient hash table. Examples include AWS, Google Cloud and…
GraphHD: Efficient graph classification using hyperdimensional computing
Igor Nunes, Mike Heddes, Tony Givargis +2
Hyperdimensional Computing (HDC) developed by Kanerva is a computational model for machine learning inspired by neuroscience. HDC exploits characteristics of biological neural syst…
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures
Mike Heddes, Igor Nunes, Pere Vergés +5
Hyperdimensional computing (HD), also known as vector symbolic architectures (VSA), is a framework for computing with distributed representations by exploiting properties of random…