Alternatives and similar repositories for kaos:

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

• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• yaoli / nade_k
  An iterative neural autoregressive distribution estimator (NADE-K)
  ☆26Updated 10 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• lisa-lab / GSN
  Efficient implementation of Generative Stochastic Networks
  ☆12Updated 11 years ago
• davidbarber / AutoDiff
  Julia AutoDiff
  ☆28Updated 8 years ago
• tonywu95 / eval_gen
  Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"
  ☆130Updated 7 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆48Updated 8 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• ml-lab / auxiliary-deep-generative-models
  Implementation of auxiliary deep generative models for semi-supervised learning
  ☆28Updated 9 years ago
• google-deepmind / mnist-cluttered
  Cluttered MNIST Dataset
  ☆50Updated 9 years ago
• pierrelux / rlss2017
  ☆17Updated 7 years ago
• jaanli / proximity_vi
  This code accompanies the proximity variational inference paper.
  ☆18Updated 6 years ago
• ericjang / variance_reduction
  Implementation of Variance Reduction Techniques in Julia
  ☆11Updated 8 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆90Updated 4 years ago
• larsmaaloee / auxiliary-deep-generative-models
  Deep generative models for semi-supervised learning.
  ☆108Updated 8 years ago
• hjweide / adversarial-autoencoder
  A Lasagne and Theano implementation of the paper Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow.
  ☆41Updated 8 years ago
• jych / cle
  ☆88Updated 8 years ago
• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 4 years ago
• jbornschein / bihm
  Bidirectional Helmholtz Machines
  ☆41Updated 9 years ago
• rdipietro / mist-rnns
  Mixed History Recurrent Neural Networks
  ☆47Updated 6 years ago
• cilvrRG / RL
  Reading Group on Reinforcement Learning topics
  ☆55Updated 8 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• albietz / stochs
  stochs: fast stochastic solvers for machine learning in C++ and Cython
  ☆26Updated 2 years ago
• RobRomijnders / VAE_rec
  Variational Recurrent Auto Encoder
  ☆15Updated 8 years ago
• nicholas-leonard / dpnn
  deep extensions to nn
  ☆23Updated 8 years ago
• Nat-D / SVAE-Torch
  ☆11Updated 8 years ago