Alternatives and similar repositories for a-nice-mc

Users that are interested in a-nice-mc are comparing it to the libraries listed below

• kefirski / bdir_vae
  simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch
  ☆52Updated 7 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆101Updated 9 years ago
• ermongroup / markov-chain-gan
  Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)
  ☆80Updated 7 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆33Updated 2 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆105Updated 7 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
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• laurent-dinh / nice
  ☆85Updated 10 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• yujiali / gmmn
  Generative moment matching networks
  ☆150Updated 8 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 6 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆182Updated 6 years ago
• taesungp / real-nvp
  Implementation of Real-NVP in Tensorflow
  ☆102Updated 6 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• bioinf-jku / coulomb_gan
  Implementation of Coulomb GANs
  ☆62Updated 3 years ago
• CW-Huang / NAF
  Experiments for the Neural Autoregressive Flows paper
  ☆124Updated 4 years ago
• ermongroup / Sequential-Variational-Autoencoder
  Implementation of Sequential Variational Autoencoder
  ☆88Updated 7 years ago
• jmtomczak / vae_vpflows
  Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling
  ☆91Updated 8 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• Bonnevie / rebar
  A Python implementation of the gradient REBAR estimator.
  ☆46Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 8 months ago