Alternatives and similar repositories for rebar:

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

• CW-Huang / torchkit
  ☆37Updated 5 years ago
• wgrathwohl / BackpropThroughTheVoidRL
  RL Experiments from our paper "Backpropagation Through the Void": https://arxiv.org/abs/1711.00123. Lovingly forked from OpenAI's RL Base…
  ☆38Updated 7 years ago
• duvenaud / relax
  Optimizing control variates for black-box gradient estimation
  ☆162Updated 5 years ago
• pemami4911 / REBAR-pytorch
  Implementation of REBAR in PyTorch
  ☆17Updated 6 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 8 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago
• ermongroup / lagvae
  Lagrangian VAE
  ☆28Updated 6 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆77Updated 2 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• zihangdai / cegan_iclr2017
  Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"
  ☆24Updated 7 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 7 years ago
• wouterkool / estimating-gradients-without-replacement
  Estimating Gradients for Discrete Random Variables by Sampling without Replacement
  ☆40Updated 5 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 4 years ago
• kefirski / bdir_vae
  simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch
  ☆52Updated 7 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆33Updated last year
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 5 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆100Updated 9 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• bioinf-jku / coulomb_gan
  Implementation of Coulomb GANs
  ☆62Updated 3 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 2 years ago
• csc2541-f17 / csc2541-f17.github.io
  ☆12Updated 7 years ago
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 5 years ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆41Updated 6 years ago
• wellecks / vaes
  Variational Autoencoders & Normalizing Flows Project
  ☆18Updated 8 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 5 years ago
• rachtsingh / lgamma
  Implementations of polygamma, lgamma, and beta functions for PyTorch
  ☆24Updated 7 years ago