ICML 2023 Topological Deep Learning Challenge:Design and Results
| Title: | ICML 2023 Topological Deep Learning Challenge:Design and Results |
|---|---|
| Authors: | Papillon, Mathilde; Hajij, Mustafa; Frantzen, Florian; Jenne, Helen; Mathe, Johan; Hoppe, Josef; Schaub, Michael T.; Papamarkou, Theodore; Guzmán-Sáenz, Aldo; Rieck, Bastian; Kvinge, Henry; Meisner, Jan; Zamzmi, Ghada; Myers, Audun; Birdal, Tolga; Dey, Tamal; Doster, Tim; Emerson, Tegan; Gopalakrishnan, Gurusankar; Govil, Devendra; Grande, Vincent; Livesay, Neal; Mukherjee, Soham; Samaga, Shreyas N.; Ramamurthy, Karthikeyan Natesan; Karri, Maneel Reddy; Rosen, Paul; Sanborn, Sophia; Scholkemper, Michael; Walters, Robin; Agerberg, Jens; Bökman, Georg; Barikbin, Sadrodin; Battiloro, Claudio; Bazhenov, Gleb; Bernardez, Guillermo; Brent, Aiden; Escalera, Sergio; Fiorellino, Simone; Gavrilev, Dmitrii; Hassanin, Mohammed; Häusner, Paul; Gardaa, Odin Hoff; Khamis, Abdelwahed; Lecha, Manuel; Magai, German; Malygina, Tatiana; Melnyk, Pavlo; Ballester, Rubén; Nadimpalli, Kalyan; Nikitin, Alexander; Rabinowitz, Abraham; Salatiello, Alessandro; Scardapane, Simone; Scofano, Luca; Singh, Suraj; Sjölund, Jens; Snopov, Pavel; Spinelli, Indro; Telyatnikov, Lev; Testa, Lucia; Yang, Maosheng; Zaghen, Olga; Zia, Ali; Yue, Yixiao; Miolane, Nina |
| Source: | Papillon, M, Hajij, M, Frantzen, F, Jenne, H, Mathe, J, Hoppe, J, Schaub, M T, Papamarkou, T, Guzmán-Sáenz, A, Rieck, B, Kvinge, H, Meisner, J, Zamzmi, G, Myers, A, Birdal, T, Dey, T, Doster, T, Emerson, T, Gopalakrishnan, G, Govil, D, Grande, V, Livesay, N, Mukherjee, S, Samaga, S N, Ramamurthy, K N, Karri, M R, Rosen, P, Sanborn, S, Scholkemper, M, Walters, R, Agerberg, J, Bökman, G, Barikbin, S, Battiloro, C, Bazhenov, G, Bernardez, G, Brent, A, Escalera, S, Fiorellino, S, Gavrilev, D, Hassanin, M, Häusner, P, Gardaa, O H, Khamis, A, Lecha, M, Magai, G, Malygina, T, .... |
| Publication Year: | 2023 |
| Collection: | The University of Manchester: Research Explorer - Publications |
| Description: | 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. |
| Document Type: | article in journal/newspaper |
| File Description: | application/pdf |
| Language: | English |
| Availability: | https://research.manchester.ac.uk/en/publications/7cd1e255-1eb6-4327-89d4-468d2bcb466b; https://pure.manchester.ac.uk/ws/files/278926322/papillon23a.pdf |
| Rights: | info:eu-repo/semantics/openAccess |
| Accession Number: | edsbas.8EFF8B44 |
| Database: | BASE |