Date/Time Date(s) - 23/10/20251:30 pm - 2:30 pm
Speaker: Dr. Nina Miolane (UC Santa Barbara)
Location: Hamilton Hall, Room 102
Title: Topological Deep Learning: Unlocking the Structure of Relational Systems
Abstract: The natural world is full of complex systems characterized by intricate relations between their components: from social interactions between individuals in a social network to electrostatic interactions between atoms in a protein. Topological Deep Learning (TDL) provides a framework to process and extract knowledge from data associated with these systems, such as predicting the social community to which an individual belongs or predicting whether a protein can be a reasonable target for drug development. By extending beyond traditional graph-based methods, TDL incorporates higher-order relational structures, providing a new lens to tackle challenges in applied sciences and beyond. This talk will introduce the core principles of TDL and provide a comprehensive review of its rapidly growing literature, with a particular focus on neural network architectures and their performance across various domains. I will present open-source implementations that make TDL methods more accessible and practical for real-world applications. All in all, this talk will showcase how TDL models can effectively capture and reason about the complexity of real-world systems, while highlighting the remaining challenges and exciting opportunities for future advancements in the field.
Hajij, M., Papillon, M., Frantzen, F., Agerberg, J., AlJabea, I., Ballester, R., … & Miolane, N. (2024). TopoX: a suite of Python packages for machine learning on topological domains. Journal of Machine Learning Research (JMLR), 25(374), 1-8.
Papamarkou, T., Birdal, T., Bronstein, M. M., Carlsson, G. E., Curry, J., Gao, Y., … & Zamzmi, G. (2024). Position: Topological Deep Learning is the New Frontier for Relational Learning. In Forty-first International Conference on Machine Learning (ICML).
Papillon, M., Bernárdez, G., Battiloro, C., & Miolane, N. (2025). TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks. In Forty-second International Conference on Machine Learning (ICML).
Papillon, M., Sanborn, S., Hajij, M., & Miolane, N. (2023). Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networks. arXiv preprint arXiv:2304.10031.
Hajij, M., Zamzmi, G., Papamarkou, T., Miolane, N., Guzmán-Sáenz, A., Ramamurthy, K. N., … & Schaub, M. T. (2022). Topological deep learning: Going beyond graph data. arXiv preprint arXiv:2206.00606.