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John N. Chiasson

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.NE3

identity via Semantic Scholar / OpenAlex

most citedContinuous Learning in a Single-Incremental-Task Scenario with Spike Features

3 citations · 3 across the 1 of their papers we have counts for

collaborators

3 papers

cs.NE2020★ 3 cited

Continuous Learning in a Single-Incremental-Task Scenario with Spike Features

Ruthvik Vaila, John Chiasson, Vishal Saxena

Deep Neural Networks (DNNs) have two key deficiencies, their dependence on high precision computing and their inability to perform sequential learning, that is, when a DNN is train…

cs.NE2020

A Deep Unsupervised Feature Learning Spiking Neural Network with Binarized Classification Layers for EMNIST Classification using SpykeFlow

Ruthvik Vaila, John Chiasson, Vishal Saxena

End user AI is trained on large server farms with data collected from the users. With ever increasing demand for IOT devices, there is a need for deep learning approaches that can…

cs.NE2019

Deep Convolutional Spiking Neural Networks for Image Classification

Ruthvik Vaila, John Chiasson, Vishal Saxena

Spiking neural networks are biologically plausible counterparts of the artificial neural networks, artificial neural networks are usually trained with stochastic gradient descent a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.