Quaternion Vector Quantized Variational Autoencoder

Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in generative tasks. However, these models still face limitations in handling complex image reconstruction, part...

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Vydané v:	IEEE signal processing letters Ročník 32; s. 151 - 155
Hlavní autori:	Luo, Hui, Liu, Xin, Sun, Jian, Zhang, Yang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Convolution Decoding Face recognition Image quality Image reconstruction Indexes Multidimensional data Neural networks Parameters Quantization (signal) quaternion generative models quaternion neural networks Quaternions Task complexity Training vector quantized variational autoencoder Vectors
ISSN:	1070-9908, 1558-2361
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