Alternatives and similar repositories for rbm-pytorch

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

• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 3 years ago
• dragen1860 / pytorch-mnist-vae
  Pytorch Implementation of variational auto-encoder for MNIST
  ☆61Updated 6 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 3 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆45Updated 2 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• swyoon / pytorch-energy-based-model
  Simple illustrative examples for energy-based models in PyTorch
  ☆66Updated 5 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆130Updated last year
• GAMES-UChile / The_Art_of_Gaussian_Processes
  ☆38Updated 3 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆121Updated 2 years ago
• djstrouse / information-bottleneck
  a python implementation of various versions of the information bottleneck, including automated parameter searching
  ☆128Updated 5 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆55Updated 3 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆85Updated 4 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 2 years ago
• GabrielBianconi / pytorch-rbm
  Restricted Boltzmann Machines (RBMs) in PyTorch
  ☆164Updated 7 years ago
• gugarosa / learnergy
  💡 Learnergy is a Python library for energy-based machine learning models.
  ☆68Updated 7 months ago
• dngfra / Restricted-Boltzmann-Machines
  Implementation of restricted Boltzmann machines in Tensorflow 2
  ☆28Updated 2 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆89Updated last year
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆91Updated 3 years ago
• acids-ircam / pytorch_flows
  Implementation and tutorials of normalizing flows with the novel distributions module
  ☆167Updated 5 years ago
• drewwilimitis / Manifold-Learning
  Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Emb…
  ☆239Updated 5 years ago
• google-deepmind / mc_gradients
  ☆170Updated last year
• facebookresearch / amortized-optimization-tutorial
  Tutorial on amortized optimization for learning to optimize over continuous domains
  ☆244Updated last week
• tk-rusch / coRNN
  Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)
  ☆50Updated 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