Alternatives and similar repositories for vilds

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

• mattjj / pyslds
  ☆96Updated 7 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 4 years ago
• catniplab / vlgp
  Dimensionality reduction of spikes trains
  ☆48Updated 3 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
• frsong / pycog
  Train excitatory-inhibitory recurrent neural networks for cognitive tasks.
  ☆50Updated 9 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 / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆111Updated 2 years ago
• mackelab / autohmm
  Hidden Markov Models (HMMs) with tied states and autoregressive observations
  ☆23Updated 4 years ago
• BouchardLab / DynamicalComponentsAnalysis
  Dynamical Components Analysis
  ☆32Updated last year
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 5 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 / pyhsmm-autoregressive
  autoregressive plugin
  ☆27Updated 2 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• mattjj / pybasicbayes
  ☆155Updated 5 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆59Updated last year
• 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
• aecker / gpfa
  Gaussian Process Factor Analysis
  ☆30Updated 9 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 11 years ago
• gamaleldin / TME
  This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified …
  ☆18Updated 7 years ago
• tachukao / mgplvm-pytorch
  ☆23Updated last year
• tejparr / nmpassing
  neuronal message passing
  ☆17Updated 6 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
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 7 years ago
• mackelab / CorBinian
  CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations
  ☆19Updated 3 years ago
• gamaleldin / CFR
  This code package is for the Corrected-Fisher-Randomization (CFR) method. This method generates random surrogate data that preserves a sp…
  ☆10Updated 7 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago