Alternatives and similar repositories for dpmm:

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

• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 4 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆48Updated last year
• SheffieldML / GPclust
  Collapsed Variational Bayes
  ☆70Updated 5 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• davidandrzej / PyIBP
  NumPy implementation of infinite latent feature model (aka Indian Buffet Process or IBP)
  ☆49Updated 7 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• HIPS / pgmult
  Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation
  ☆61Updated 4 years ago
• rgiordan / LinearResponseVariationalBayesNIPS2015
  Code and text for our NIPS 2015 paper on linear response variational Bayes
  ☆19Updated 7 years ago
• gelman / ep-stan
  ☆32Updated 4 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆38Updated 8 years ago
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 5 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• rachtsingh / ibp_vae
  mean-field and structured VAEs for the IBP
  ☆23Updated 7 years ago
• aschein / pgds
  Poisson-Gamma dynamical systems
  ☆16Updated 8 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 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
• jameshensman / GPclust
  Clustering time series using Gaussian processes and Variational Bayes.
  ☆39Updated 4 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆26Updated 5 years ago
• STOR-i / sgmcmc
  sgmcmc: a stochastic gradient MCMC package for R
  ☆29Updated 4 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• mijungi / lllvm
  ☆16Updated 9 years ago