Alternatives and similar repositories for pytorch-rbm

Users that are interested in pytorch-rbm are comparing it to the libraries listed below

• wmingwei / restricted-boltzmann-machine-deep-belief-network-deep-boltzmann-machine-in-pytorch
  ☆52Updated 7 years ago
• mehulrastogi / Deep-Belief-Network-pytorch
  This repository has implementation and tutorial for Deep Belief Network
  ☆101Updated 6 years ago
• odie2630463 / Restricted-Boltzmann-Machines-in-pytorch
  RBM in Pytorch
  ☆58Updated 8 years ago
• ReyhaneAskari / pytorch_experiments
  Auto Encoders in PyTorch
  ☆63Updated 7 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆88Updated 6 years ago
• sksq96 / pytorch-vae
  A CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch
  ☆300Updated 5 years ago
• schelotto / Wasserstein-AutoEncoders
  PyTorch implementation of Wasserstein Auto-Encoders
  ☆295Updated 4 years ago
• atinghosh / VAE-pytorch
  Variational auto encoder in pytorch
  ☆56Updated 6 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 5 years ago
• dragen1860 / pytorch-mnist-vae
  Pytorch Implementation of variational auto-encoder for MNIST
  ☆62Updated 6 years ago
• djstrouse / information-bottleneck
  a python implementation of various versions of the information bottleneck, including automated parameter searching
  ☆128Updated 5 years ago
• gtoubassi / mnist-vae
  Semi-supervised learning with mnist using variational autoencoders. An unsupervised representation is learned which allows for superior …
  ☆33Updated 7 years ago
• giannisnik / som
  Pytorch implementation of a Self-Organizing Map
  ☆88Updated 6 years ago
• MasanoriYamada / Mine_pytorch
  MINE: Mutual Information Neural Estimation in pytorch (unofficial)
  ☆204Updated 6 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• maitek / waae-pytorch
  Wasserstein Adversarial Autoencoder Pytorch
  ☆27Updated 7 years ago
• nicola-decao / s-vae-pytorch
  Pytorch implementation of Hyperspherical Variational Auto-Encoders
  ☆370Updated 5 years ago
• nicola-decao / s-vae-tf
  Tensorflow implementation of Hyperspherical Variational Auto-Encoders
  ☆232Updated 6 years ago
• MarcCote / NADE
  Neural Autoregressive Distribution Estimation
  ☆53Updated 8 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆208Updated 4 years ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆236Updated 6 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆152Updated 5 years ago
• psanch21 / VAE-GMVAE
  This repository contains the implementation of the VAE and Gaussian Mixture VAE using TensorFlow and several network architectures
  ☆210Updated 5 years ago
• RuiShu / vae-clustering
  Unsupervised clustering with (Gaussian mixture) VAEs
  ☆298Updated 8 years ago
• ericjang / normalizing-flows-tutorial
  Tutorial on normalizing flows.
  ☆299Updated 7 years ago
• gpapamak / maf
  Masked Autoregressive Flow
  ☆213Updated 11 months ago
• ethanluoyc / pytorch-vae
  A Variational Autoencoder (VAE) implemented in PyTorch
  ☆425Updated 3 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆89Updated 6 years ago