Alternatives and similar repositories for papers

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

• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 11 years ago
• stepelu / ptstat
  Probabilistic Programming and Statistical Inference in PyTorch
  ☆111Updated 8 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 8 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 7 years ago
• blei-lab / publications
  The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).
  ☆72Updated 8 years ago
• DeNeutoy / bayesian-rnn
  ☆62Updated 8 years ago
• LucaAmbrogioni / GP-CaKe-project
  Bayesian Effective Connectivity
  ☆54Updated 7 years ago
• echen / dirichlet-process
  Introduction to Nonparametric Bayes, Infinite Mixture Models, and the Dirichlet Process (+ McDonald's)
  ☆306Updated 10 years ago
• edwardlib / observations
  Tools for loading standard data sets in machine learning
  ☆206Updated 3 years ago
• dustinvtran / bayesrl
  A Python library for reinforcement learning using Bayesian approaches
  ☆53Updated 10 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 9 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆76Updated 5 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• mariru / exponential_family_embeddings
  Bernoulli Embeddings for Text
  ☆84Updated 8 years ago
• gradientinstitute / aboleth
  A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
  ☆128Updated 4 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆191Updated 6 years ago
• tbroderick / bnp_tutorial
  ☆30Updated 8 years ago
• inf16nyu / home
  ☆78Updated 9 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• ferrine / gelato
  Bayesian dessert for Lasagne
  ☆83Updated 8 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago
• powerscorinne / GLRM
  ☆99Updated 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 5 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆67Updated 8 years ago
• uvadlc / uvadlc_practicals_2016
  Repository for practical assignments for UvA Deep Learning Course 2016
  ☆51Updated 8 years ago
• shakedshammah / failures_of_DL
  ☆90Updated 8 years ago
• approximateinference / approximateinference.github.io
  ProbML: Symposium on Probabilistic Machine Learning
  ☆50Updated this week
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆47Updated 9 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆109Updated 7 years ago