Alternatives and similar repositories for pgm

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

• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated last year
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• MauroCE / PythonBRMLtoolbox
  Python 3.7 version of David Barber's MATLAB BRMLtoolbox
  ☆25Updated 6 years ago
• anhncs / Probabilistic-Graphical-Models
  Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
  ☆104Updated 12 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 5 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 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
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆92Updated 4 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆67Updated 6 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆132Updated 6 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 7 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated 2 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 9 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 5 years ago
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆95Updated 2 years ago
• sailinglab / pgm-spring-2019
  Course webpage for PGM, Spring 2019.
  ☆76Updated 4 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 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
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆68Updated 7 years ago
• hottbox / hottbox-tutorials
  HOTTBOX: Higher Order Tensors ToolBOX. Tutorials
  ☆38Updated 2 years ago
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• AmazaspShumik / Mixture-Models
  Hierarchical Mixture of Experts,Mixture Density Neural Network
  ☆45Updated 8 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• ritchieng / eigenvectors-from-eigenvalues
  PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.
  ☆99Updated 3 years ago
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆59Updated 4 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆48Updated 8 years ago