Alternatives and similar repositories for GMM

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

• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆95Updated 8 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆64Updated 2 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆122Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆45Updated 10 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
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• shaobohan / VariationalGaussianCopula
  Matlab Code for Variational Gaussian Copula Inference
  ☆16Updated 9 years ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆69Updated 6 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• simonkamronn / kvae
  Kalman Variational Auto-Encoder
  ☆138Updated 6 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆102Updated 7 years ago
• LCAS / RKN
  ☆47Updated 3 years ago
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 3 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 4 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 8 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆103Updated last year
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆56Updated 7 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆82Updated 6 years ago
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆35Updated 6 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆93Updated last year
• hiroyuki-kasai / RSOpt
  Riemannian stochastic optimization algorithms: Version 1.0.3
  ☆67Updated 2 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆141Updated 9 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆212Updated 5 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• wangshusen / RandMatrixMatlab
  simple MATLAB code for randomized matrix computation
  ☆23Updated 10 years ago