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
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated 10 months ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆91Updated 4 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated 2 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 5 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆62Updated 8 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
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• 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 10 years ago
• tbroderick / bnp_tutorial
  ☆30Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 7 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• siemens / policy_search_bb-alpha
  ☆68Updated 6 years ago
• hrayrhar / T-CorEx
  Implementation of linear CorEx and temporal CorEx.
  ☆37Updated 3 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆66Updated 6 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 5 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago