Alternatives and similar repositories for variational-gaussian-mixture:

Users that are interested in variational-gaussian-mixture are comparing it to the libraries listed below

• brendanhasz / svi-gaussian-mixture-model
  Notebook fitting a Bayesian Gaussian mixture model via stochastic variational inference w/ TensorFlow 2.0
  ☆14Updated 5 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆86Updated 3 years ago
• zhd96 / ds-hdp-hmm
  Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
  ☆26Updated 4 years ago
• acerbilab / vbmc
  Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
  ☆222Updated last year
• luiscarlosgph / t-Student-Mixture-Models
  Implementation of the paper: 'Robust mixture modelling using the t distribution', D. Peel and G. J. McLachlan.
  ☆29Updated last year
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆51Updated 4 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆120Updated 5 years ago
• shreyas253 / variational_NP_BMM
  The source code is related to our work- Shreyas Seshadri, Ulpu Remes and Okko Rasanen: "Dirichlet process mixture models for clustering i…
  ☆10Updated 7 years ago
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆58Updated 4 years ago
• VBayesLab / VBLab
  Official documentation
  ☆28Updated 3 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 5 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆62Updated last month
• bayinf / awesome-variational-inference
  A curated list of awesome variational inference
  ☆20Updated 4 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆72Updated 3 years ago
• DanieleGammelli / DeepKalmanFilter
  Pyro/Pytorch implementation of Deep Kalman FIlter for shared-mobility demand prediction
  ☆44Updated 5 years ago
• juanjogg1987 / Fully_Natural_Gradient_HetMOGP
  This is a repositoy with a Fully Natural Gradient Scheme for Improving optimisation of the HetMOGP Model
  ☆10Updated 4 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆168Updated 10 months 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
• e-hulten / maf
  PyTorch implementation of the Masked Autoregressive Flow
  ☆24Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• jmeyers314 / DPMM
  Dirichlet Process Mixture Models
  ☆22Updated 8 years ago
• rflamary / nonconvex-optimization
  Matlab/Octave toolbox for nonconvex optimization
  ☆50Updated 8 years ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆42Updated 2 years ago
• jacobnzw / SSMToybox
  Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature
  ☆13Updated 3 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• kamdh / tvart
  Time-varying Autoregression with Low Rank Tensors
  ☆15Updated 3 years ago
• kasparmartens / c-GPLVM
  PyTorch implementation of the Covariate-GPLVM
  ☆26Updated 4 years ago