https://github.com/mfreidank/pysgmcmc
Bayesian Deep Learning with Stochastic Gradient MCMC Methods
https://github.com/mfreidank/pysgmcmc
bayesian-inference markov-chain-monte-carlo mcmc python stochastic tensorflow
Last synced: 2 months ago
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Bayesian Deep Learning with Stochastic Gradient MCMC Methods
- Host: GitHub
- URL: https://github.com/mfreidank/pysgmcmc
- Owner: MFreidank
- Created: 2017-09-04T15:55:00.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2021-09-06T08:30:19.000Z (almost 4 years ago)
- Last Synced: 2025-04-30T20:06:57.929Z (2 months ago)
- Topics: bayesian-inference, markov-chain-monte-carlo, mcmc, python, stochastic, tensorflow
- Language: Python
- Homepage:
- Size: 12.1 MB
- Stars: 39
- Watchers: 3
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
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README
========
PYSGMCMC
========
|Build Status|
|Docs_|
|Coverage_|
|Codacy_|
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 `_ that provides:
* efficient numerical computation via data flow graphs
* flexible computation environments (CPU/GPU support, desktop/server/mobile device support)
* Linear algebra operations
.. |Build Status| image:: https://travis-ci.org/MFreidank/pysgmcmc.svg?branch_master
:target: https://travis-ci.org/MFreidank/pysgmcmc
.. |Docs_| image:: https://readthedocs.org/projects/pysgmcmc/badge/?version=latest
:target: http://pysgmcmc.readthedocs.io/en/latest/
:alt: Docs
.. |Coverage_| image:: https://coveralls.io/repos/github/MFreidank/pysgmcmc/badge.svg
:target: https://coveralls.io/github/MFreidank/pysgmcmc
:alt: Coverage
.. |Codacy_| image:: https://api.codacy.com/project/badge/Grade/94a3778e36814055ad7b12875857d15e
:target: https://www.codacy.com/app/MFreidank/pysgmcmc?utm_source=github.com&utm_medium=referral&utm_content=MFreidank/pysgmcmc&utm_campaign=Badge_Grade
:alt: Codacy
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/.