Alternatives and similar repositories for ds-hdp-hmm:

Users that are interested in ds-hdp-hmm are comparing it to the libraries listed below

• jamesross2 / Bayesian-HMM
  A non-parametric Bayesian approach to Hidden Markov Models
  ☆87Updated last year
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• mattjj / pyslds
  ☆94Updated 6 years ago
• davidzoltowski / ssmdm
  Recurrent state-space models for decision making
  ☆30Updated 2 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆47Updated 8 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• nbfigueroa / ICSC-HMM
  Toolbox for IBP Coupled SPCM-CRP Hidden Markov Model. Also contains code for EM-based HMM learning and inference for Bayesian non-paramet…
  ☆15Updated 6 years ago
• 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
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• markkho / msdm
  Models of Sequential Decision-Making
  ☆45Updated 3 months ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆64Updated 2 years ago
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆109Updated last year
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆91Updated 3 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 6 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 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
• Mogeng / IOHMM
  Input Output Hidden Markov Model (IOHMM) in Python
  ☆165Updated 10 months ago
• dimarkov / aibandits
  Active inference implementation of dynamic multi-armed bandits
  ☆19Updated last year
• 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
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 4 years ago
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆117Updated 2 months ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• kamdh / tvart
  Time-varying Autoregression with Low Rank Tensors
  ☆15Updated 3 years ago
• likang7 / variational-dpgmm
  Variational Dirichlet Process Gaussian Mixture Models
  ☆29Updated 10 years ago
• marineschimel / ilqr_vae
  ☆11Updated 2 years ago
• aidanscannell / mogpe
  Mixtures of Gaussian Process Experts in GPflow/TensorFlow
  ☆11Updated 2 years ago
• earcher / vilds
  Black box variational inference for state space models
  ☆1Updated 8 years ago
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆31Updated last year
• fmorenopino / HeterogeneousHMM
  Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…
  ☆77Updated last year
• epfl-lasa / changepoint-detection
  Online Change-point Detection Algorithm for Multi-Variate Data: Applications on Human/Robot Demonstrations.
  ☆45Updated 7 years ago