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

- Hannouch, Khalil; Chalup, Stephan

Title
Supplementary material of the paper: Learning To See Topological Properties In 4D Using Convolutional Neural Networks
Creator
Hannouch, Khalil; Chalup, Stephan
Relation
ARC
Relation
G2000134
Publisher Link
http://dx.doi.org/10.25817/GMW8-Q849
Resource Type
dataset
Date
2023
Description
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.
Subject
Betti numbers; manifolds; 4-dimensional images; convolutional neural network; topological data analysis; INFORMATION AND COMPUTING SCIENCES; MATHEMATICAL SCIENCES; ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING; Computer Vision; Neural, Evolutionary and Fuzzy Computation; Pattern Recognition and Data Mining; Topology
Identifier
http://hdl.handle.net/1959.13/1477380
Identifier
uon:49972
Rights
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 and the paper with title 'Learning To See Topological Properties In 4D Using Convolutional Neural Networks', provide a link to the Creative Commons license, and indicate if changes were made.
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ATTACHMENT03 Movie $size HTML Document
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