Pytorch Implementation of "Neural Discrete Representation Learning"
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Updated
Mar 23, 2018 - Jupyter Notebook
Pytorch Implementation of "Neural Discrete Representation Learning"
Tensorflow implementation of VQVAE for voice conversion
A Chainer implementation of VQ-VAE.
PyTorch implementation of VQ-VAE applied on CIFAR10 dataset
PyTorch implementation of VQ-VAE + WaveNet by [Chorowski et al., 2019] and VQ-VAE on speech signals by [van den Oord et al., 2017]
Pytorch implementation of "Group Latent Embedding for Vector Quantized Variational Autoencoder in Non-Parallel Voice Conversion" [Interspeech 2019]
Variational autoencoders implemented in Tensorflow.
PyTorch implementation of VQ-VAE by Aäron van den Oord et al.
Implementation of a multi-modal VQ-VAE
A PyTorch implementation of "Continuous Relaxation Training of Discrete Latent Variable Image Models"
Vector-Quantized Contrastive Predictive Coding for Acoustic Unit Discovery and Voice Conversion
Keras Implementation of Vector Quantizer Variational AutoEncoder (VQ-VAE)
Minimalist implementation of VQ-VAE in Pytorch
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
PyTorch Implementation of Vector Quantized Variational AutoEncoders.
생성모델을 이용한 ASMR 컨텐츠 제작 프로젝트
Signal Processing with Python and Librosa
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