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 …

Hyperdimensional (HD) computing is built upon its unique data type referred to as
hypervectors. The dimension of these hypervectors is typically in the range of tens of …

Hyperdimensional computing is an emerging computational framework that takes inspiration
from attributes of neuronal circuits including hyperdimensionality, fully distributed …

Memorization is an essential functionality that enables today's machine learning algorithms
to provide a high quality of learning and reasoning for each prediction. Memorization gives …

This article reviews recent progress in the development of the computing framework vector
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …

Vector space models for symbolic processing that encode symbols by random vectors have
been proposed in cognitive science and connectionist communities under the names Vector …

Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …

Research, the universal pursuit of new knowledge, is embarking on a fresh journey into
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …

Recently, brain-inspired computing models have shown great potential to outperform today's
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …

Variable binding is a cornerstone of symbolic reasoning and cognition. But how binding can
be implemented in connectionist models has puzzled neuroscientists, cognitive …