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vae
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Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
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Jan 31, 2019 - Python
Collection of generative models in Tensorflow
tensorflow
gan
mnist
infogan
generative-model
vae
ebgan
generative-adversarial-networks
wgan
cvae
lsgan
variational-autoencoder
began
cgan
wgan-gp
generative-models
dragan
acgan
fashion-mnist
improved-wgan
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Jul 21, 2018 - Python
DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。
dcgan
vae
image-generation
pix2pix
image-to-image
nerual-style
cycle-gan
deepface
deepfakes
tensorflow2
style-gan
deepnude
zao
sin-gan
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Jul 12, 2020 - Python
A Collection of Variational Autoencoders (VAE) in PyTorch.
deep-learning
reproducible-research
architecture
pytorch
vae
beta-vae
paper-implementations
gumbel-softmax
celeba-dataset
wae
variational-autoencoders
pytorch-implementation
dfc-vae
iwae
vqvae
vae-implementation
pytorch-vae
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Mar 22, 2020 - Python
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
learning
machine-learning
deep-neural-networks
deep-learning
tensorflow
deep
pytorch
vae
unsupervised-learning
variational-inference
probabilistic-graphical-models
variational-autoencoder
autoregressive-neural-networks
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Mar 30, 2020 - Python
Advanced Deep Learning with Keras, published by Packt
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May 6, 2020 - Python
でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet
machine-learning
deep-learning
neural-network
chainer
tensorflow
keras
pytorch
dcgan
vae
seq2seq
machinelearning
deeplearning
ga
wgan
wgan-gp
xception
seq2seq-attention
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Jul 4, 2020 - Jupyter Notebook
A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
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Apr 18, 2017 - Python
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
python
machine-learning
pytorch
discriminator
generative-adversarial-network
gan
infogan
autoencoder
vae
wasserstein
wgan
lsgan
began
generative-models
dragan
fishergan
mmgan
nsgan
ragan
fgan
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Nov 19, 2018 - Jupyter Notebook
PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349
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Jul 15, 2020 - Python
Tensorflow implementation of variational auto-encoder for MNIST
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Apr 11, 2017 - Python
Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟
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Apr 2, 2019 - Jupyter Notebook
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
reinforcement-learning
deep-learning
robotics
deep-reinforcement-learning
openai-gym
pytorch
generative-adversarial-network
gan
openai
dqn
gym
policy-gradient
vae
ddpg
vae-gan
variational-autoencoder
mujoco
mujoco-py
experience-replay
rl-algorithms
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Jul 14, 2019 - Python
Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
tutorial
course
deep-learning
neural-network
mooc
tensorflow
word2vec
gan
dcgan
pixelcnn
vae
glove
wavenet
magenta
autoregressive
celeba
conditional
vae-gan
cyclegan
nsynth
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Jan 28, 2020 - Python
Vector Quantized VAEs - PyTorch Implementation
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Jul 23, 2019 - Python
Recurrent Variational Autoencoder that generates sequential data implemented with pytorch
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Mar 15, 2017 - Python
Dataset to assess the disentanglement properties of unsupervised learning methods
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Jun 2, 2017 - Jupyter Notebook
Experiments for understanding disentanglement in VAE latent representations
deep-learning
reproducible-research
pytorch
mnist
chairs-dataset
vae
representation-learning
unsupervised-learning
beta-vae
celeba
variational-autoencoder
disentanglement
dsprites
fashion-mnist
disentangled-representations
factor-vae
beta-tcvae
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Nov 29, 2019 - Python
Pytorch implementation of β-VAE
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Nov 28, 2018 - Python
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
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Apr 25, 2019 - Jupyter Notebook
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
deep-learning
generative-model
vae
awesome-list
representation-learning
unsupervised-learning
variational-inference
variational-autoencoder
variational-bayes
disentanglement
variational-auto-encoder
disentangled-representations
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Jul 14, 2020
A tensorflow implementation of "Generating Sentences from a Continuous Space"
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Jul 14, 2018 - Python
Pytorch implementation of Hyperspherical Variational Auto-Encoders
machine-learning
deep-learning
pytorch
vae
manifold-learning
variational-autoencoder
von-mises-fisher
hyperspherical-vae
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Mar 21, 2020 - Python
Stochastic Adversarial Video Prediction
generative-adversarial-network
gan
stochastic
vae
adversarial
vae-gan
variational-autoencoder
video-generation
video-prediction
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Oct 8, 2019 - Python
Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).
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Apr 5, 2018 - Jupyter Notebook
Minimalist implementation of VQ-VAE in Pytorch
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Oct 2, 2019 - Python
Replicating "Understanding disentangling in β-VAE"
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Jun 2, 2018 - Python
Tensorflow implementation of Hyperspherical Variational Auto-Encoders
machine-learning
deep-learning
tensorflow
citation
vae
manifold-learning
variational-autoencoder
von-mises-fisher
nicolas
hyperspherical-vae
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Dec 1, 2018 - Python
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This is an awesome library, thanks @ddbourgin!!
Users might not know the best way to install this package and try it out. (I didn't, so I eventually just copied the source files.)
Neither the readme nor readthedocs have install instructions.
I couldn't find it on PyPi or Anaconda, and there doesn't appear to be a
pyproject.toml,setup.cfg,setup.py, or conda recipe.Moreover, the t