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Title: GitHub - lts129/generative-models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. · GitHub

Open Graph Title: GitHub - lts129/generative-models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

X Title: GitHub - lts129/generative-models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Description: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. - lts129/generative-models

Open Graph Description: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. - lts129/generative-models

X Description: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. - lts129/generative-models

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GANhttps://github.com/lts129/generative-models/tree/master/GAN
GANhttps://github.com/lts129/generative-models/tree/master/GAN
HelmholtzMachinehttps://github.com/lts129/generative-models/tree/master/HelmholtzMachine
HelmholtzMachinehttps://github.com/lts129/generative-models/tree/master/HelmholtzMachine
RBMhttps://github.com/lts129/generative-models/tree/master/RBM
RBMhttps://github.com/lts129/generative-models/tree/master/RBM
VAEhttps://github.com/lts129/generative-models/tree/master/VAE
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https://github.com/lts129/generative-models#generative-models
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https://github.com/lts129/generative-models#whats-in-it
https://github.com/lts129/generative-models#generative-adversarial-nets-gan
Vanilla GANhttps://arxiv.org/abs/1406.2661
Conditional GANhttps://arxiv.org/abs/1411.1784
InfoGANhttps://arxiv.org/abs/1606.03657
Wasserstein GANhttps://arxiv.org/abs/1701.07875
Mode Regularized GANhttps://arxiv.org/abs/1612.02136
Coupled GANhttps://arxiv.org/abs/1606.07536
Auxiliary Classifier GANhttps://arxiv.org/abs/1610.09585
Least Squares GANhttps://arxiv.org/abs/1611.04076v2
Boundary Seeking GANhttps://arxiv.org/abs/1702.08431
Energy Based GANhttps://arxiv.org/abs/1609.03126
f-GANhttps://arxiv.org/abs/1606.00709
Generative Adversarial Parallelizationhttps://arxiv.org/abs/1612.04021
DiscoGANhttps://arxiv.org/abs/1703.05192
Adversarial Feature Learninghttps://arxiv.org/abs/1605.09782
Adversarially Learned Inferencehttps://arxiv.org/abs/1606.00704
Boundary Equilibrium GANhttps://arxiv.org/abs/1703.10717
Improved Training for Wasserstein GANhttps://arxiv.org/abs/1704.00028
DualGANhttps://arxiv.org/abs/1704.02510
MAGAN: Margin Adaptation for GANhttps://arxiv.org/abs/1704.03817
Softmax GANhttps://arxiv.org/abs/1704.06191
GibbsNethttps://papers.nips.cc/paper/7094-gibbsnet-iterative-adversarial-inference-for-deep-graphical-models.pdf
https://github.com/lts129/generative-models#variational-autoencoder-vae
Vanilla VAEhttps://arxiv.org/abs/1312.6114
Conditional VAEhttps://arxiv.org/abs/1406.5298
Denoising VAEhttps://arxiv.org/abs/1511.06406
Adversarial Autoencoderhttps://arxiv.org/abs/1511.05644
Adversarial Variational Bayeshttps://arxiv.org/abs/1701.04722
https://github.com/lts129/generative-models#restricted-boltzmann-machine-rbm
Binary RBM with Contrastive Divergencehttp://www.cs.toronto.edu/~fritz/absps/cdmiguel.pdf
Binary RBM with Persistent Contrastive Divergencehttp://www.cs.toronto.edu/~tijmen/pcd/pcd.pdf
https://github.com/lts129/generative-models#helmholtz-machine
Binary Helmholtz Machine with Wake-Sleep Algorithmhttp://www.cs.toronto.edu/~fritz/absps/ws.pdf
https://github.com/lts129/generative-models#dependencies
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