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
ICML 2023 topological deep learning challenge. Design and results / Papillon, Mathilde; Hajij, Mustafa; Frantzen, Florian; Hoppe, Josef; Jenne, Helen; Mathe, Johan; Myers, Audun; Papamarkou, Theodore; Schaub, Michael T.; Zamzmi, Ghada; Birdal, Tolga; Dey, Tamal; Doster, Timothy; Emerson, Tegan H.; Gopalakrishnan, Gurusankar; Govil, D.; Grande, Vincent P.; Guzm'an-S'aenz, Aldo; Kvinge, Henry; Livesay, Neal; Meisner, Jan; Mukherjee, Soham; Samaga, Shreyas N.; Natesan Ramamurthy, Karthikeyan; Reddy Karri, Maneel; Rosen, Paul; Sanborn, Sophia; Scholkemper, Michael; Walters, Robin; Agerberg, Jens; Bokman, Georg; Barikbin, Sadrodin; Battiloro, Claudio; Bazhenov, Gleb; Bern('a)rdez, Guillermo; Brent, Aiden; Escalera, Sergio; Fiorellino, Simone; Gavrilev, Dmitrii; Hassanin, Mohammed; Hausner, Paul; Hoff Gardaa, Odin; Khamis, Abdelwahed; Lecha, M; Magai, German; Malygina, Tatiana; Melnyk, Pavlo; Ballester, Rub('e)n; Varma Nadimpalli, Kalyan; Nikitin, Alexander; Rabinowitz, Abraham; Salatiello, Alessandro; Scardapane, Simone; Scofano, Luca; Singh, Suraj; Sjolund, Jens; Snopov, Paul; Spinelli, Indro; Telyatnikov, Lev; Testa, Lucia; Yang, Maosheng; Yue, Yixiao; Zaghen, Olga; Zia, Ali; Miolane, Nina. - 221:(2023), pp. 3-8. (Intervento presentato al convegno 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning, TAG-ML 2023, held at the International Conference on Machine Learning, ICML 2023 tenutosi a Honolulu; Hawaii).
ICML 2023 topological deep learning challenge. Design and results
Claudio Battiloro;Simone Fiorellino;Simone Scardapane;Luca Scofano;Indro Spinelli;Lev Telyatnikov;Lucia Testa;
2023
Abstract
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| File | Dimensione | Formato | |
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