Alternatives and similar repositories for Copula-Variational-Bayes

Users that are interested in Copula-Variational-Bayes are comparing it to the libraries listed below

• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆45Updated 7 years ago
• gpstuff-dev / gpstuff
  GPstuff - Gaussian process models for Bayesian analysis
  ☆175Updated 2 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• danilkuzin / GP-EnKF
  Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…
  ☆17Updated 7 years ago
• Sohl-Dickstein / Hamiltonian-Annealed-Importance-Sampling
  Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…
  ☆26Updated 11 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 4 years ago
• hiroyuki-kasai / RSOpt
  Riemannian stochastic optimization algorithms: Version 1.0.3
  ☆67Updated 2 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆19Updated 4 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆116Updated 12 years ago
• duvenaud / harlemcmc-shake
  Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.
  ☆36Updated 11 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 years ago
• keskarnitish / minSQN
  Optimization using Stochastic quasi-Newton methods
  ☆42Updated 8 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 9 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• cvxgrp / ncvx
  ☆77Updated 3 years ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆33Updated 5 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆30Updated 3 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• acerbilab / vbmc
  Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
  ☆232Updated 2 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆34Updated 8 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆52Updated 10 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• gpeyre / 2017-ot-beginners
  Optimal Transport for Dummies - Code, slides and article
  ☆33Updated 8 years ago
• SimonDu / CUR-matrix-decomposition
  A matlab library for CUR matrix decomposition
  ☆27Updated 8 years ago
• n-takeishi / bayesiandmd
  Bayesian Dynamic Mode Decomposition (Bayesian DMD)
  ☆18Updated 3 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 7 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 11 months ago