Skip to main content

No project description provided

Project description

UT-LVCE: Perturbations and Causality in Gaussian Latent Variable Models

This repository contains a Python implementation of the UT-LVCE algorithms from the 2022 paper "Perturbations and Causality in Gaussian Latent Variable Models", by A. Taeb, JL. Gamella, C. Heinze-Deml and P. Bühlmann.

It is also available as the python package utlvce. You can find the full documentation at https://utlvce.readthedocs.io/en/latest/.

The code to reproduce the experiments and figures in the paper can be found in a separate repository.

Installation

You can clone this repo or install the package using pip:

pip install utlvce

Documentation

You can find the docs at https://utlvce.readthedocs.io/en/latest/.

Versioning

The pacakge is still at its infancy and its API may change in the future. Non backward-compatible changes to the API are reflected by a change to the minor or major version number, e.g.

code written using utlvce==0.1.2 will run with utlvce==0.1.3, but may not run with utlvce==0.2.0.

Feedback

Feedback is most welcome! You can add an issue or send an email.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

utlvce-0.1.1.tar.gz (44.3 kB view hashes)

Uploaded Source

Built Distribution

utlvce-0.1.1-py3-none-any.whl (46.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page