Alternatives and similar repositories for mixest

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

• aki-nishimura / discontinuous-hmc
  "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu
  ☆27Updated 6 years ago
• pierrejacob / winference
  R package to perform statistical inference in generative models using the Wasserstein distance (requires CGAL)
  ☆25Updated 5 years ago
• hanyas / mimo
  A toolbox for inference of mixture models
  ☆16Updated last year
• SamDuffield / mocat
  All things Monte Carlo, written in JAX.
  ☆30Updated 2 years ago
• ganguli-lab / proxalgs
  Proximal algorithms and operators in python
  ☆26Updated 6 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 5 years ago
• arviz-devs / simuk
  Simulation based calibration and generation of synthetic data.
  ☆50Updated last month
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 6 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆18Updated 5 years ago
• ASPP / ASPP-2018-dataviz
  Material for the Advanced Scientific Programming in Python course on data visualization
  ☆17Updated 6 years ago
• robsalomone / Deep-Probabilistic-Models-Course
  Deep Probabalistic Models: Materials for my course for the Australian Mathematical Sciences Institute (AMSI) Winter School 2021
  ☆11Updated 3 years ago
• cjones6 / cubic_reg
  Implementation of Nesterov and Polyak's (2006) cubic regularization algorithm and Cartis et al's (2011) adaptive cubic regularization alg…
  ☆18Updated 3 years ago
• evdoxiataka / ipme
  An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".
  ☆24Updated 11 months ago
• markusheinonen / adaptivegp
  Fully nonstationary, heteroscedastic GP for Matlab
  ☆14Updated 9 months ago
• tszanalytics / BayesTesting.jl
  ☆15Updated 5 years ago
• twgr / ccfs
  Canonical Correlation Forests
  ☆20Updated 6 years ago
• cvxgrp / a2dr
  Anderson accelerated Douglas-Rachford splitting
  ☆29Updated 4 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• aki-nishimura / NUTS-matlab
  ☆16Updated 8 years ago
• mijungi / lllvm
  ☆16Updated 9 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated 10 months ago
• gpeyre / 2017-ot-beginners
  Optimal Transport for Dummies - Code, slides and article
  ☆32Updated 7 years ago
• gpschool / gpss20
  Gaussian Process and Uncertainty Quantification Summer School 2020
  ☆33Updated 2 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆30Updated 2 years ago
• ssm-jax / ssm-book
  Interactive textbook on state space models
  ☆12Updated 3 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• stephenbeckr / zeroSR1
  Proximal gradient algorithm for convex optimization, using a diagonal +/- rank-1 norm
  ☆21Updated 4 months ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago