Supplementary material of the paper: Learning To See Topological Properties In 4D Using Convolutional Neural Networks

Thu 22 Jun 2023 18:56:02 AEST

This record contains supplementary material associated with the paper: Khalil Mathieu Hannouch, Stephan Chalup. Learning To See Topological Properties In 4D Using Convolutional Neural Networks. 2nd Annual Topology, Algebra, and Geometry in Machine Learning Workshop at ICML. PMLR 2023. The supplement comprises Code, Data set and Movie.

4D 128 cube topological dataset

Fri 17 Nov 2023 11:41:11 AEDT

The materials in this repository comprise a 4D topological dataset and two 4D visualisations in video format. The dataset can be downloaded directly as a series of twenty 1.5GB .zip files. More details can be found in the README.txt file. This data is also available via mediated access in the following formats: A single file approximately 30GB .zip file, or a series of ten 3GB .zip files.

All code and data released with this supplementary material uses the following license: Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0 This license permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors & provide a link to the Creative Commons license, and indicate if changes were made.

Please contact researchdata@newcastle.edu.au to access the data in alternative formats.