Alternatives and similar repositories for pgm:

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

• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆90Updated 4 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆47Updated 8 months ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 5 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 9 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆43Updated 6 years ago
• AmazaspShumik / Mixture-Models
  Hierarchical Mixture of Experts,Mixture Density Neural Network
  ☆45Updated 7 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆64Updated 6 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• rfeinman / learning-to-learn
  Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
  ☆21Updated 6 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated 2 years ago
• muupan / deep-ensemble-uncertainty
  An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)
  ☆34Updated 8 years ago
• mebden / GPtutorial
  Matlab code for the introduction to Gaussian processes, 2008
  ☆30Updated 9 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆38Updated 5 years ago
• anhncs / Probabilistic-Graphical-Models
  Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
  ☆105Updated 11 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 9 years ago
• PhDP / mlbop
  Matlab code for S. Theodoridis' "Machine Learning: A Bayesian and Optimization Perspective" (2015).
  ☆66Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• kaiu85 / hm-rnn
  PyTorch Implementation of Hierarchical Multiscale Recurrent Neural Networks
  ☆15Updated 6 years ago
• vsuriya93 / Deep-Learning-for-Graph-Representations
  This contains my M.Tech project work on using Deep Leanring for learning graph representations. Data will be provided on request
  ☆33Updated 7 years ago
• rubinxin / FITBO
  Code for Fast Information-theoretic Bayesian Optimisation
  ☆16Updated 6 years ago
• MauroCE / PythonBRMLtoolbox
  Python 3.7 version of David Barber's MATLAB BRMLtoolbox
  ☆24Updated 6 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆38Updated 8 years ago
• dustinvtran / bayesrl
  A Python library for reinforcement learning using Bayesian approaches
  ☆54Updated 9 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago
• zjost / bayesian-linear-regression
  A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/
  ☆82Updated 8 years ago