Dynamical System Autoencoders

Autoencoders represent a significant category of deep learning models and are widely utilized for dimensionality reduction. However, standard Autoencoders are complicated architectures that normally have several layers and many hyper-parameters that require tuning. In this paper, we introduce a new...

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Bibliographic Details

Published in:	Proceedings (IEEE International Conference on Emerging Technologies and Factory Automation) pp. 1496 - 1503
Main Authors:	He, Shiquan, Paffenroth, Randy, Cava, Olivia, Dunham, Cate
Format:	Conference Proceeding
Language:	English
Published:	IEEE 18.12.2024
Subjects:	autoencoder Autoencoders denoising Dimensionality reduction dynamical system autoencoder Dynamical systems Encoding Iterative methods Noise reduction sparse autoencoder Sparse matrices stacked autoencoder supervised autoencoder Training Tuning
ISSN:	1946-0759
Online Access:	Get full text
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