yunjhongwu / Sticky-HDPHMM-demo

Related projects ⓘ

Alternatives and complementary repositories for Sticky-HDPHMM-demo

• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆65Updated 7 years ago
• SheffieldML / GPclust
  Collapsed Variational Bayes
  ☆67Updated 5 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 10 years ago
• dustinvtran / bayesrl
  A Python library for reinforcement learning using Bayesian approaches
  ☆52Updated 9 years ago
• michaelchughes / NPBayesHMM
  Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…
  ☆77Updated 6 years ago
• hannawallach / dpmm
  Dirichlet process mixture model.
  ☆26Updated 10 years ago
• mattjj / pyslds
  ☆90Updated 6 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆81Updated 4 years ago
• tbroderick / bnp_tutorial
  ☆29Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• kzhai / PyNPB
  Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).
  ☆73Updated 9 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
• yaringal / CLGP
  Categorical Latent Gaussian Process
  ☆16Updated 9 years ago
• mwhoffman / pygp
  Python package for inference with Gaussian processes
  ☆11Updated 9 years ago
• blei-lab / zero-inflated-embedding
  Code for the icml paper "zero inflated exponential family embedding"
  ☆29Updated 7 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆62Updated last year
• jameshensman / GPclust
  Clustering time series using Gaussian processes and Variational Bayes.
  ☆39Updated 4 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• rgiordan / LinearResponseVariationalBayesNIPS2015
  Code and text for our NIPS 2015 paper on linear response variational Bayes
  ☆19Updated 6 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 9 years ago
• mattjj / pybasicbayes
  ☆153Updated 5 years ago
• albietz / dpmm
  Variational inference for Dirichlet process mixture models with multinomial mixture components.
  ☆32Updated 10 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆48Updated 7 months ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• aschein / pgds
  Poisson-Gamma dynamical systems
  ☆16Updated 7 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 12 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated last year
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 7 years ago
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated last year