Alternatives and similar repositories for Bayesian-HMM

Users that are interested in Bayesian-HMM are comparing it to the libraries listed below

• mattjj / pyslds
  ☆96Updated 7 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 7 years ago
• fmorenopino / HeterogeneousHMM
  Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…
  ☆79Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 5 months 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
• Mogeng / IOHMM
  Input Output Hidden Markov Model (IOHMM) in Python
  ☆168Updated last year
• zhd96 / ds-hdp-hmm
  Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
  ☆30Updated 4 years ago
• fdtomasi / regain
  REGAIN (Regularised Graphical Inference)
  ☆29Updated 2 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated 2 years ago
• jvkersch / hsmmlearn
  A library for hidden semi-Markov models with explicit durations
  ☆85Updated 3 years ago
• asnelt / mixedvines
  Python package for canonical vine copula trees with mixed continuous and discrete marginals
  ☆47Updated last year
• paulbrodersen / entropy_estimators
  Estimators for the entropy and other information theoretic quantities of continuous distributions
  ☆141Updated last year
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 2 years ago
• nickc1 / skccm
  Convergent Cross Mapping in Scikit Learn's style
  ☆98Updated 5 years ago
• HHalva / hmnlica
  Code for Hidden Markov Nonlinear ICA
  ☆24Updated 3 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• gatsby-sahani / gp-sde
  ☆14Updated 2 years ago
• michaelchughes / NPBayesHMM
  Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…
  ☆78Updated 7 years ago
• kormilitzin / the-signature-method-in-machine-learning
  Foundations and Applications
  ☆98Updated 5 years ago
• lopatovsky / HMMs
  Continuous-time Hidden Markov Model
  ☆102Updated last year
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• acerbilab / vbmc
  Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
  ☆226Updated 2 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆101Updated 8 months ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• TyXe-BDL / TyXe
  ☆152Updated 2 years ago
• tingiskhan / pyfilter
  Particle filtering and sequential parameter inference in Python
  ☆83Updated 2 years ago
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆120Updated 5 months ago