Alternatives and similar repositories for pyhsmm-autoregressive:

Users that are interested in pyhsmm-autoregressive are comparing it to the libraries listed below

• mattjj / pybasicbayes
  ☆154Updated 5 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 6 years ago
• mattjj / pyslds
  ☆94Updated 6 years ago
• slinderman / thesis
  My PhD Thesis
  ☆22Updated 8 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆60Updated 8 years ago
• earcher / vilds
  Black box variational inference for state space models
  ☆1Updated 8 years ago
• slinderman / pyhsmm_spiketrains
  Code for fitting neural spike trains with nonparametric hidden Markov and semi-Markov models built upon mattjj's PyHSMM framework.
  ☆14Updated 6 years ago
• slinderman / pyglm
  Interpretable neural spike train models with fully-Bayesian inference algorithms
  ☆47Updated 6 years ago
• mackelab / autohmm
  Hidden Markov Models (HMMs) with tied states and autoregressive observations
  ☆23Updated 4 years ago
• jameshensman / GPclust
  Clustering time series using Gaussian processes and Variational Bayes.
  ☆39Updated 4 years ago
• robince / pyentropy
  Information Theoretic Tools for Python
  ☆91Updated 5 years ago
• ganguli-lab / twpca
  🕝 Time-warped principal components analysis (twPCA)
  ☆125Updated 3 years ago
• catniplab / vlgp
  Dimensionality reduction of spikes trains
  ☆49Updated 3 years ago
• slinderman / theano_pyglm
  Generalized linear models for neural spike train modeling, in Python! With GPU-accelerated fully-Bayesian inference, MAP inference, and n…
  ☆44Updated 10 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
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 4 years ago
• dicai / bayesCPD
  changepoint detection for Bayesian models
  ☆21Updated 10 years ago
• tomwallis / glm-intro
  A collection of IPython notebooks from a graduate-level statistics course run by Tom Wallis and Philipp Berens
  ☆27Updated 9 years ago
• patrickmineault / xcorr-notebooks
  An ongoing collection of ipython notebooks on neuroscience from xcorr: computational neuroscience.
  ☆78Updated 2 years ago
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 4 years ago
• JackKelly / bayesianchangepoint
  An implementation of Adams & MacKay 2007 "Bayesian Online Changepoint Detection"
  ☆31Updated 10 years ago
• SheffieldML / GPclust
  Collapsed Variational Bayes
  ☆70Updated 5 years ago
• skggm / skggm
  Scikit-learn compatible estimation of general graphical models
  ☆247Updated last year
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆74Updated 7 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 4 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• DrugowitschLab / VBLinLogit
  Variational Bayes linear and logistic regression
  ☆34Updated 5 years ago
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆106Updated last year
• glm-tools / pyglmnet
  Python implementation of elastic-net regularized generalized linear models
  ☆280Updated last year