TopoX: A Suite of Python Packages for Machine Learning on Topological Domains

Mustafa Hajij et al.

We introduce topox, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. topox consists of three packages: toponetx facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; topoembedx provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; topomodelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains.
Full article Code 
@misc{hajij2024topox,
title={TopoX: A Suite of Python Packages for Machine Learning on Topological Domains},
author={Mustafa Hajij and Mathilde Papillon and Florian Frantzen and Jens Agerberg and Ibrahem AlJabea and Ruben Ballester and Claudio Battiloro and Guillermo Bernárdez and Tolga Birdal and Aiden Brent and Peter Chin and Sergio Escalera and Simone Fiorellino and Odin Hoff Gardaa and Gurusankar Gopalakrishnan and Devendra Govil and Josef Hoppe and Maneel Reddy Karri and Jude Khouja and Manuel Lecha and Neal Livesay and Jan Meißner and Soham Mukherjee and Alexander Nikitin and Theodore Papamarkou and Jaro Prílepok and Karthikeyan Natesan Ramamurthy and Paul Rosen and Aldo Guzmán-Sáenz and Alessandro Salatiello and Shreyas N. Samaga and Simone Scardapane and Michael T. Schaub and Luca Scofano and Indro Spinelli and Lev Telyatnikov and Quang Truong and Robin Walters and Maosheng Yang and Olga Zaghen and Ghada Zamzmi and Ali Zia and Nina Miolane},
year={2024},
eprint={2402.02441},
archivePrefix={arXiv},
primaryClass={cs.LG} }