Pysgmcmc Save

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

Project README

======== PYSGMCMC

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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:

.. code-block:: python

sample, cost = next(sampler)

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

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Install

The quick way::

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

Documentation

Our documentation can be found at http://pysgmcmc.readthedocs.io/en/latest/.

Open Source Agenda is not affiliated with "Pysgmcmc" Project. README Source: MFreidank/pysgmcmc
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