A survey on hyperdimensional computing aka vector symbolic architectures, part i: Models and data transformations
This two-part comprehensive survey is devoted to a computing framework most commonly
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …
A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges
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 …
commonly known under the names Hyperdimensional Computing and Vector Symbolic …
The relational bottleneck as an inductive bias for efficient abstraction
A central challenge for cognitive science is to explain how abstract concepts are acquired
from limited experience. This has often been framed in terms of a dichotomy between …
from limited experience. This has often been framed in terms of a dichotomy between …
Classification using hyperdimensional computing: A review
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 …
hypervectors. The dimension of these hypervectors is typically in the range of tens of …
Vector symbolic architectures as a computing framework for emerging hardware
This article reviews recent progress in the development of the computing framework vector
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …
symbolic architectures (VSA)(also known as hyperdimensional computing). This framework …
Torchhd: An open source python library to support research on hyperdimensional computing and vector symbolic architectures
Hyperdimensional computing (HD), also known as vector symbolic architectures (VSA), is a
framework for computing with distributed representations by exploiting properties of random …
framework for computing with distributed representations by exploiting properties of random …
Learning from hypervectors: A survey on hypervector encoding
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 …
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …
Unpaired image translation via vector symbolic architectures
Image-to-image translation has played an important role in enabling synthetic data for
computer vision. However, if the source and target domains have a large semantic …
computer vision. However, if the source and target domains have a large semantic …
Understanding hyperdimensional computing for parallel single-pass learning
Hyperdimensional computing (HDC) is an emerging learning paradigm that computes with
high dimensional binary vectors. There is an active line of research on HDC in the …
high dimensional binary vectors. There is an active line of research on HDC in the …
Hyperdimensional computing as a framework for systematic aggregation of image descriptors
P Neubert, S Schubert - … of the IEEE/CVF conference on …, 2021 - openaccess.thecvf.com
Image and video descriptors are an omnipresent tool in computer vision and its application
fields like mobile robotics. Many hand-crafted and in particular learned image descriptors …
fields like mobile robotics. Many hand-crafted and in particular learned image descriptors …