Skip to main content

Rotation-Invariant Hyperspherical Variational Convolutional Autoencoder

Project description

Build Status Documentation Status versions

Spherinator & HiPSter

Spherinator uses PyTorch Lightning to implement a convolutional neural network (CNN) based variational autoencoder (VAE) with a spherical latent space. HiPSter creates the HiPS tilings and the catalog which can be visualized interactively on the surface of a sphere with Aladin Lite.

Installation

Poetry is used for installation.

poetry install

Documentation

Read The Docs

Acknowledgments

Funded by the European Union. This work has received funding from the European High-Performance Computing Joint Undertaking (JU) and Belgium, Czech Republic, France, Germany, Greece, Italy, Norway, and Spain under grant agreement No 101093441.

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European High Performance Computing Joint Undertaking (JU) and Belgium, Czech Republic, France, Germany, Greece, Italy, Norway, and Spain. Neither the European Union nor the granting authority can be held responsible for them.

License

This project is licensed under the Apache-2.0 License.

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

spherinator-0.3.0.tar.gz (305.5 kB view hashes)

Uploaded Source

Built Distribution

spherinator-0.3.0-py3-none-any.whl (39.2 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