#1Minimalist implementation of VQ-VAE in Pytorch - GitHub

This is an implementation of the VQ-VAE (Vector Quantized Variational Autoencoder) and Convolutional Varational Autoencoder. from Neural Discrete ...

於github.com

#2vq-vae.ipynb - Colaboratory

The VQ-VAE uses a discrete latent representation mostly because many important ... I have followed the code from the TensorFlow implementation by the author ...

於colab.research.google.com

#3Vector-Quantized Variational Autoencoders - Keras

VQ -VAE was proposed in Neural Discrete Representation Learning by van der Oord et al. In traditional VAEs, the latent space is continuous and is ...

於keras.io

#4VQ VAE: Models, code, and papers - CatalyzeX

The Vector Quantized-Variational Autoencoder (VQ-VAE) [1] provides an unsupervised model for learning discrete representations by combining vector quantization ...

於www.catalyzex.com

#5Understanding VQ-VAE (DALL-E Explained Pt. 1) - ML@B Blog

During training, VQ-VAE assumes a uniform prior over all the latent codes, so all latents are considered equally likely. Additionally the ...

於ml.berkeley.edu

#6Supervised Vector Quantized Variational Autoencoder ... - arXiv

the utility of S-VQ-VAE on a machine learning benchmark dataset, the MNIST dataset, ... the code can be well interpreted after the training converges.

於arxiv.org

#7Keras VQ-VAE for image generation | Kaggle

Explore and run machine learning code with Kaggle Notebooks | Using data from mnist.npz.

於www.kaggle.com

#8Neural Discrete Representation Learning - VQ-VAEs - YouTube

於www.youtube.com

#9VQ-VAE implementation / pytorch - ReposHub

VQ -VAE implementation / pytorch,VQ-VAE. ... Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes.

於reposhub.com

#10Predicting Video with VQVAE | OpenReview

With VQ-VAE we compress high-resolution videos into a hierarchical set of ... Code Of Ethics: I acknowledge that I and all co-authors of this work have read ...

於openreview.net