ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Hajij, Mustafa, Helen Jenne, Mathe, Johan, Audun Myers, Papamarkou, Theodore, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gopalakrishnan, Gurusankar, Govil, Devendra, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Karri, Maneel Reddy, Paul A. Rosen · arXiv (Cornell University) · 2023
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two-month duration. This paper describes the design of the challenge and summarizes its main findings.