Alternatives and similar repositories for MINE

Users that are interested in MINE are comparing it to the libraries listed below

• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆68Updated 4 years ago
• Alfo5123 / Variational-Sparse-Coding
  Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge
  ☆62Updated 2 years ago
• kamenbliznashki / generative_models
  Pytorch implementations of generative models: VQVAE2, AIR, DRAW, InfoGAN, DCGAN, SSVAE
  ☆92Updated 4 years ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆84Updated 6 years ago
• fjxmlzn / PacGAN
  [NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
  ☆81Updated 4 years ago
• anonymous-iclr-2019 / acai-iclr-2019
  Anonymized code for ICLR 2019 submission "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"
  ☆20Updated 6 years ago
• ermongroup / flow-gan
  Code for "Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models", AAAI 2018.
  ☆109Updated 7 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆152Updated 5 years ago
• eelxpeng / UnsupervisedDeepLearning-Pytorch
  This repository tries to provide unsupervised deep learning models with Pytorch
  ☆90Updated 7 years ago
• izmailovpavel / flowgmm
  ☆148Updated 3 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 7 years ago
• AMLab-Amsterdam / DIVA
  Implementation of 'DIVA: Domain Invariant Variational Autoencoders'
  ☆104Updated 5 years ago
• addtt / ladder-vae-pytorch
  Ladder Variational Autoencoders (LVAE) in PyTorch
  ☆92Updated 5 years ago
• atinghosh / VAE-pytorch
  Variational auto encoder in pytorch
  ☆57Updated 6 years ago
• matthew-liu / beta-vae
  A Pytorch Implementation of the Beta-VAE
  ☆44Updated 6 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• yookoon / VLAE
  Code for Variational Laplace Autoencoders
  ☆54Updated 2 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• lin-shuyu / ladder-latent-data-distribution-modelling
  In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…
  ☆41Updated 4 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• dilinwang820 / nonlinear_svgd
  Nonlinear SVGD for Learning Diversified Mixture Models
  ☆13Updated 6 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• MasanoriYamada / Mine_pytorch
  MINE: Mutual Information Neural Estimation in pytorch (unofficial)
  ☆205Updated 6 years ago