15 citations · 44 across the 13 of their papers we have counts for
8 papers · 1 filter
Advancing Intoxication Detection: A Smartwatch-Based Approach
Manuel Segura, Pere Vergés, Richard Ky +7
Excess alcohol consumption leads to serious health risks and severe consequences for both individuals and their communities. To advocate for healthier drinking habits, we introduce…
Enhanced Detection of Transdermal Alcohol Levels Using Hyperdimensional Computing on Embedded Devices
Manuel E. Segura, Pere Verges, Justin Tian Jin Chen +6
Alcohol consumption has a significant impact on individuals' health, with even more pronounced consequences when consumption becomes excessive. One approach to promoting healthier…
Molecular Classification Using Hyperdimensional Graph Classification
Pere Verges, Igor Nunes, Mike Heddes +2
Our work introduces an innovative approach to graph learning by leveraging Hyperdimensional Computing. Graphs serve as a widely embraced method for conveying information, and their…
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration
Mike Heddes, Narayan Srinivasa, Tony Givargis +1
The excessive computational requirements of modern artificial neural networks (ANNs) are posing limitations on the machines that can run them. Sparsification of ANNs is often motiv…
HDCC: A Hyperdimensional Computing compiler for classification on embedded systems and high-performance computing
Pere Vergés, Mike Heddes, Igor Nunes +2
Hyperdimensional Computing (HDC) is a bio-inspired computing framework that has gained increasing attention, especially as a more efficient approach to machine learning (ML). This…
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…
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…