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 2 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆48Updated 8 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆66Updated 2 years ago
• sorooshafiee / WKF
  ☆15Updated 6 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• mattjj / pyslds
  ☆96Updated 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
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆92Updated 3 years ago
• Mogeng / IOHMM
  Input Output Hidden Markov Model (IOHMM) in Python
  ☆167Updated 11 months 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
• 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
• davidzoltowski / ssmdm
  Recurrent state-space models for decision making
  ☆30Updated 2 years ago
• EEA-sensors / Bayesian-Filtering-and-Smoothing
  Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson
  ☆73Updated last year
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• marineschimel / ilqr_vae
  ☆11Updated 2 years ago
• danilkuzin / GP-EnKF
  Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…
  ☆17Updated 6 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆51Updated 9 years ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆33Updated 4 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 7 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated 2 years ago
• chengl7 / LonGP
  Gaussian process regression + automatical model selection for logitudinal -omics data
  ☆21Updated 4 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
• aicherc / sgmcmc_ssm_code
  Python code for SGMCMC for Time Series SSMs
  ☆12Updated 4 years ago
• gatsby-sahani / gp-sde
  ☆14Updated last year
• tingiskhan / pyfilter
  Particle filtering and sequential parameter inference in Python
  ☆83Updated 2 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆66Updated 4 months ago
• strongio / torchcast
  Forecasting with PyTorch
  ☆54Updated 2 weeks ago
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆111Updated 2 years ago