Alternatives and similar repositories for tree_structured_rslds

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

• earcher / vilds
  Black box variational inference for state space models
  ☆2Updated 9 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
• mattjj / pyslds
  ☆96Updated 7 years ago
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 5 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
• gatsby-sahani / gp-sde
  ☆14Updated 2 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆61Updated last year
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆111Updated 2 years ago
• BouchardLab / DynamicalComponentsAnalysis
  Dynamical Components Analysis
  ☆32Updated 2 years ago
• slinderman / stats215
  ☆30Updated 5 years ago
• davidzoltowski / ssmdm
  Recurrent state-space models for decision making
  ☆30Updated 2 years ago
• zhenwendai / RGP
  Python library for Recurrent Gaussian Processes
  ☆20Updated 7 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 7 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆40Updated 5 years ago
• slinderman / thesis
  My PhD Thesis
  ☆22Updated 9 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• jimmysmith1919 / JSLDS_public
  ☆12Updated 3 years ago
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆33Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆70Updated 4 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• mackelab / autohmm
  Hidden Markov Models (HMMs) with tied states and autoregressive observations
  ☆23Updated 5 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 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
• hichamjanati / spatio-temporal-alignements
  Spatio-temporal alignements: Optimal transport in space and time
  ☆47Updated 3 months ago
• dimarkov / aibandits
  Active inference implementation of dynamic multi-armed bandits
  ☆19Updated last month
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 5 years ago