pyknos 0.16.0

don't regress. A package for neural conditional density estimation.

Description

Python package for conditional density estimation. It either wraps or implements diverse conditional density estimators.

Density estimation with normalizing flows

This package provides pass-through access to all the functionalities of nflows.

Installation

pyknos requires Python 3.8 or higher. A GPU is not required, but can lead to speed-up in some cases. We recommend using a conda virtual environment (Miniconda installation instructions). If conda is installed on the system, an environment for installing pyknos can be created as follows:

$ conda create -n pyknos_env python=3.12 && conda activate pyknos_env

Independent of whether you are using conda or not, pyknos can be installed using pip:

pip install pyknos

Examples

See the sbi repository for examples of using pyknos.

Name

pyknós (πυκνός) is the transliterated Greek root for density (pyknótita) and also means sagacious.

Copyright notice

This program is free software: you can redistribute it and/or modify it under the terms of the Apache License 2.0., see LICENSE for more details.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

Acknowledgments

Thanks to Artur Bekasov, Conor Durkan and George Papamarkarios for their work on nflows.

The MDN implementation in this package is based on Conor M. Durkan's.