Alternatives and similar repositories for pyslds

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

• earcher / vilds
  Black box variational inference for state space models
  ☆1Updated 8 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 6 years ago
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆109Updated 2 years ago
• mattjj / pybasicbayes
  ☆155Updated 5 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 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
• 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
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 5 years ago
• catniplab / vlgp
  Dimensionality reduction of spikes trains
  ☆49Updated 3 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆74Updated 7 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• mattjj / pyhsmm-autoregressive
  autoregressive plugin
  ☆27Updated 2 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 / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 4 years ago
• slinderman / thesis
  My PhD Thesis
  ☆22Updated 9 years ago
• davidzoltowski / ssmdm
  Recurrent state-space models for decision making
  ☆30Updated 2 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆66Updated 3 months ago
• BouchardLab / DynamicalComponentsAnalysis
  Dynamical Components Analysis
  ☆32Updated last year
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• tachukao / mgplvm-pytorch
  ☆23Updated last year
• 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
• mackelab / autohmm
  Hidden Markov Models (HMMs) with tied states and autoregressive observations
  ☆23Updated 4 years ago
• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆70Updated 3 years ago
• frsong / pycog
  Train excitatory-inhibitory recurrent neural networks for cognitive tasks.
  ☆49Updated 9 years ago
• SheffieldML / GPclust
  Collapsed Variational Bayes
  ☆70Updated 5 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆47Updated 8 years ago
• jameshensman / pythonGPLVM
  Implementation of the GPLVM algorithm in python
  ☆44Updated 15 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆59Updated 10 months ago