Metadata-Version: 2.1
Name: flow-torch
Version: 0.1.1
Summary: Normalizing Flow models in PyTorch
Home-page: https://github.com/aparafita/flow
Author: Álvaro Parafita
Author-email: parafita.alvaro@gmail.com
License: MIT
Download-URL: https://github.com/aparafita/flow/archive/v0.1.1.tar.gz
Description: 
        # flow
        
        This project implements basic Normalizing Flows in PyTorch 
        and provides functionality for defining your own easily, 
        following the conditioner-transformer architecture.
        
        This is specially useful for lower-dimensional flows and for learning purposes.
        Nevertheless, work is being done on extending its functionalities 
        to also accomodate for higher dimensional flows.
        
        Supports conditioning flows, meaning, learning probability distributions
        conditioned by a given conditioning tensor. 
        Specially useful for modelling causal mechanisms.
        
        For more information, 
        please look at our [Github page](https://github.com/aparafita/flow).
        
Keywords: flow,density,estimation,sampling,probability,distribution
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
