We investigate the task of retrieving information from compositional
dis...
Complex visual scenes that are composed of multiple objects, each with
a...
Spiking Neural Networks (SNNs) have attracted the attention of the deep
...
In this paper, we present an approach to integer factorization using
dis...
The biologically inspired spiking neurons used in neuromorphic computing...
Vector space models for symbolic processing that encode symbols by rando...
This article reviews recent progress in the development of the computing...
Many neural network models have been successful at classification proble...
Various non-classical approaches of distributed information processing, ...
Symbolic reasoning and neural networks are often considered incompatible...
The ability to encode and manipulate data structures with distributed ne...
Neuromorphic computing applies insights from neuroscience to uncover
inn...
The deployment of machine learning algorithms on resource-constrained ed...
We describe a type of neural network, called a Resonator Circuit, that
f...
Information coding by precise timing of spikes can be faster and more
en...
To accommodate structured approaches of neural computation, we propose a...
To understand cognitive reasoning in the brain, it has been proposed tha...