Alternatives and similar repositories for NPEET_LNC

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

• 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
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 5 years ago
• mattjj / pyslds
  ☆98Updated 7 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆83Updated 5 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆90Updated 7 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆37Updated 5 years ago
• mstrazar / mklaren
  A Python Multiple kernel learning library.
  ☆57Updated 6 years ago
• erichson / ristretto
  Randomized Dimension Reduction Library
  ☆117Updated 4 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• mijungi / lllvm
  ☆16Updated 9 years ago
• wgao9 / knnie
  k-Nearest Neighbor Information Estimator
  ☆26Updated 6 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• pmelchior / proxmin
  Proximal optimization in pure python
  ☆118Updated 3 years ago
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆45Updated 4 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
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 8 years ago
• SheffieldML / GPclust
  Collapsed Variational Bayes
  ☆72Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 7 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 8 months ago
• acerbilab / vbmc
  Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
  ☆229Updated 2 years ago
• davidandrzej / PyIBP
  NumPy implementation of infinite latent feature model (aka Indian Buffet Process or IBP)
  ☆51Updated 7 years ago
• DrugowitschLab / VBLinLogit
  Variational Bayes linear and logistic regression
  ☆34Updated 6 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 4 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago