Metadata-Version: 1.2
Name: eeyore
Version: 0.0.17
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/v0.0.17.tar.gz
Description: ![](https://github.com/papamarkou/eeyore/workflows/eeyore/badge.svg)
        
        MCMC methods for neural networks.
        
        eeyore can be installed using pip or anaconda. The anaconda installation does not include ODE modelling functionalilty based on torchdiffeq.
        
        To install eeyore using pip, run
        ```
        pip install eeyore
        ```
        
        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
        ```
        
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
