Data Generation with Variational Autoencoders and Generative Adversarial Networks

The paper considers the problem of modelling the distribution of data with noise in the input data. In this paper, we consider encoders and decoders, which solve the problem of modelling data distribution. The improvement of variational autoencoders (VAEs) is discussed. Practical implementation is p...

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Bibliographic Details

Published in:	Engineering Proceedings
Main Authors:	Daniil Devyatkin, Ivan Trenev
Format:	Article
Language:	English
Published:	MDPI AG 2023-06-01
Subjects:	machine learning deep learning autoencoders generative adversarial network MNIST
Online Access:	https://www.mdpi.com/2673-4591/33/1/37