Alternatives and similar repositories for learn-discrete

Users that are interested in learn-discrete are comparing it to the libraries listed below

• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 6 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 3 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• ericjang / nf-jax
  Normalizing Flows in Jax
  ☆107Updated 5 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆194Updated 2 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 7 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆184Updated 7 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆76Updated 5 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 7 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 5 years ago
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 5 years ago
• PrincetonLIPS / reversible-inductive-construction
  Discrete Object Generation with Reversible Inductive Construction (NeurIPS 2019)
  ☆30Updated 4 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 6 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆47Updated 7 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆102Updated 7 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 6 years ago
• ermongroup / BiasAndGeneralization
  ☆28Updated 6 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆74Updated 9 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆21Updated 7 years ago
• akosiorek / forge
  Basic experiment framework for tensorflow.
  ☆91Updated 4 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 3 years ago