Metadata-Version: 2.1
Name: eeyore
Version: 0.0.11
Summary: MCMC methods for neural networks
Home-page: https://github.com/papamarkou/eeyore
Author: Theodore Papamarkou
Author-email: theodore.papamarkou@gmail.com
License: MIT
Download-URL: https://github.com/papamarkou/eeyore/archive/v0.0.11.tar.gz
Keywords: Bayesian,deep learning,Markov chains,MCMC,Monte Carlo,neural networks
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.6
Requires-Dist: numpy (>=1.19.2)
Requires-Dist: torch (>=1.6.0)
Requires-Dist: torchdiffeq (>=0.1.1)
Requires-Dist: kanga (>=0.0.15)

![](https://github.com/papamarkou/eeyore/workflows/eeyore/badge.svg)

MCMC methods for neural networks.

To install eeyore using anaconda, firstly add the required channels by running
```
conda config --add channels pytorch
conda config --add channels conda-forge
```
and subsequently run
```
conda install -c papamarkou eeyore
```
To install eeyore using anaconda without adding any channels, run
```
conda install -c papamarkou -c pytorch -c conda-forge eeyore
```

To install eeyore using pip, run
```
pip install eeyore
```


