Code underlying: Hodge-Aware Convolutional Learning on Simplicial Complexes

DOI:10.4121/979541fe-e72a-42eb-af86-8dad211656bb.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/979541fe-e72a-42eb-af86-8dad211656bb

Datacite citation style

Yang, Maosheng (2025): Code underlying: Hodge-Aware Convolutional Learning on Simplicial Complexes . Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/979541fe-e72a-42eb-af86-8dad211656bb.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

This implements the convolutional neural network models on simplicial complexes, including applications of simplex-prediction and trajectory prediction.

History

  • 2025-05-26 first online, published, posted

Publisher

4TU.ResearchData

Format

script/.py

Associated peer-reviewed publication

Convolutional Learning on Simplicial Complexes

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/82579c3e-d7a1-46c4-b7ba-a5357a1c61dc.git "Learning_on_SCs"

Or download the latest commit as a ZIP.