作为Comate,由文心一言驱动的智能编程助手,我将为你详细解答关于Vector Quantized Variational Autoencoder(VQ-VAE)的问题。 1. 变分自编码器(Variational Autoencoder, VAE) 变分自编码器是一种生成模型,旨在学习数据的有效表示(编码)和从这些表示中生成新数据(解码)。与传统的自编码器不同,VAE通过引入潜在空间的概率...
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, particularly in...
This is a PyTorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937). You can find the author'soriginal implementation in Tensorflow herewithan example you can run in a Jupyter notebook. Installing Dependencies ...