# PYSGMCMC – Stochastic Gradient Markov Chain Monte Carlo Sampling¶

This package provides out-of-the-box implementations of various state-of-the-art Stochastic Gradient Markov Chain Monte Carlo sampling methods.

## PYSGMCMC¶

PYSGMCMC is a Python framework for Bayesian Deep Learning that focuses on Stochastic Gradient Markov Chain Monte Carlo methods.

# Features¶

• Complex samplers as black boxes, computing the next sample with corresponding costs of any MCMC sampler is as easy as:
sample, cost = next(sampler)

• Based on tensorflow that provides:
• efficient numerical computation via data flow graphs
• flexible computation environments (CPU/GPU support, desktop/server/mobile device support)
• Linear algebra operations

# Install¶

The quick way:

pip3 install git+https://github.com/MFreidank/pysgmcmc