Bundle Networks

This repository consists of code that accompanies the paper

Nico Courts and Henry Kvinge. Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. In International Conference on Learning Representations, 2022 (to appear).

A preprint of this work can be found on arXiv.

Organization

In this repository, one can find several folders

• bundlenet contains the code for our BundleNet model as well as the CGAN/WGAN implementations used in our paper. This is also where one can find our evaluation and training scripts.
• datasets contains all data splits used for training and evaluation. These files can be loaded directly using the torch.load method.
• notebooks consists of Jupyter notebooks that demonstrate the use of the library.

Working with BundleNets

To install on your computer, first clone this repository then navigate to this folder and execute pip install -e ./.