pierrejacob / couplingsmontecarloLinks
some scripts for the couplings enthusiasts!
☆32Updated 5 years ago
Alternatives and similar repositories for couplingsmontecarlo
Users that are interested in couplingsmontecarlo are comparing it to the libraries listed below
Sorting:
- Database with posteriors of interest for Bayesian inference☆209Updated last month
- A simple library to run variational inference on Stan models.☆33Updated 2 years ago
- Efficient, lightweight variational inference and approximation bounds☆45Updated last year
- Unbiased Markov chain Monte Carlo with couplings☆30Updated 3 years ago
- Posterior with interesting shapes from actually used models☆13Updated 7 months ago
- Some teaching material and other educational resources☆41Updated last month
- ☆56Updated 3 years ago
- Course material for the PhD course in Advanced Bayesian Learning☆59Updated 7 months ago
- Self-tuning HMC algorithms and evaluations☆19Updated 11 months ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆28Updated 7 years ago
- Markov chain Monte Carlo general, and Hamiltonian Monte Carlo specific, diagnostics for Stan☆88Updated 2 months ago
- ☆16Updated 5 months ago
- BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.☆105Updated 3 weeks ago
- probabilistic programming focused on fun☆42Updated last month
- Just a little MCMC☆231Updated last year
- Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave☆77Updated last year
- Integrals of Gaussians under linear domain constraints☆15Updated 5 years ago
- ☆24Updated 2 years ago
- R-package for building and fitting Bayesian ODE models in Stan☆29Updated last year
- Bayesian Regression Models in Pyro☆72Updated last year
- Tutorials and sampling algorithm comparisons☆77Updated this week
- sgmcmc: a stochastic gradient MCMC package for R☆30Updated 4 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 5 years ago
- Book Chapter Drafts☆35Updated last year
- Unbiased MCMC with couplings☆19Updated 6 years ago
- Bayesian inference and posterior analysis for Python☆46Updated last year
- A library for bayesian variable selection☆31Updated 8 months ago
- This tutorial is a basic guide to understanding the Zig-Zag Sampling method. This document is released with the aim of diffusion and shar…☆21Updated 6 years ago
- State of the art inference for your bayesian models.☆222Updated 5 months ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆26Updated 6 years ago