E. Paxon Frady | DeepAI

AI Chat

Featured Co-authors

Friedrich T. Sommer
24 publications
Denis Kleyko
23 publications
Abbas Rahimi
21 publications
Mike Davies
20 publications
Bruno A. Olshausen
18 publications
Garrick Orchard
13 publications
Jan M. Rabaey
12 publications
Evgeny Osipov
8 publications
Sumit Bam Shrestha
6 publications
Amir Khosrowshahi
5 publications
Sophia Sanborn
5 publications

∙ 05/26/2023

Efficient Decoding of Compositional Structure in Holistic Representations

We investigate the task of retrieving information from compositional dis...

0 Denis Kleyko, et al. ∙

∙ 03/23/2023

Learning and generalization of compositional representations of visual scenes

Complex visual scenes that are composed of multiple objects, each with a...

0 E. Paxon Frady, et al. ∙

∙ 04/01/2022

Deep Learning in Spiking Phasor Neural Networks

Spiking Neural Networks (SNNs) have attracted the attention of the deep ...

0 Connor Bybee, et al. ∙

∙ 03/02/2022

Integer Factorization with Compositional Distributed Representations

In this paper, we present an approach to integer factorization using dis...

0 Denis Kleyko, et al. ∙

∙ 11/05/2021

Efficient Neuromorphic Signal Processing with Loihi 2

The biologically inspired spiking neurons used in neuromorphic computing...

0 Garrick Orchard, et al. ∙

∙ 09/08/2021

Computing on Functions Using Randomized Vector Representations

Vector space models for symbolic processing that encode symbols by rando...

31 E. Paxon Frady, et al. ∙

∙ 06/09/2021

Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware

This article reviews recent progress in the development of the computing...

0 Denis Kleyko, et al. ∙

∙ 12/14/2020

Perceptron Theory for Predicting the Accuracy of Neural Networks

Many neural network models have been successful at classification proble...

0 Denis Kleyko, et al. ∙

∙ 10/07/2020

Cellular Automata Can Reduce Memory Requirements of Collective-State Computing

Various non-classical approaches of distributed information processing, ...

0 Denis Kleyko, et al. ∙

∙ 09/14/2020

Variable Binding for Sparse Distributed Representations: Theory and Applications

Symbolic reasoning and neural networks are often considered incompatible...

0 E. Paxon Frady, et al. ∙

∙ 07/07/2020

Resonator networks for factoring distributed representations of data structures

The ability to encode and manipulate data structures with distributed ne...

0 E. Paxon Frady, et al. ∙

∙ 04/27/2020

Neuromorphic Nearest-Neighbor Search Using Intel's Pohoiki Springs

Neuromorphic computing applies insights from neuroscience to uncover inn...

0 E. Paxon Frady, et al. ∙

∙ 09/19/2019

Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks

The deployment of machine learning algorithms on resource-constrained ed...

0 Denis Kleyko, et al. ∙

∙ 06/19/2019

Resonator Circuits for factoring high-dimensional vectors

We describe a type of neural network, called a Resonator Circuit, that f...

0 Spencer J. Kent, et al. ∙

∙ 01/23/2019

Robust computation with rhythmic spike patterns

Information coding by precise timing of spikes can be faster and more en...

0 E. Paxon Frady, et al. ∙

∙ 02/28/2018

A theory of sequence indexing and working memory in recurrent neural networks

To accommodate structured approaches of neural computation, we propose a...

0 E. Paxon Frady, et al. ∙

∙ 07/05/2017

Theory of the superposition principle for randomized connectionist representations in neural networks

To understand cognitive reasoning in the brain, it has been proposed tha...

0 E. Paxon Frady, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world