Martin Carrasco, Guillermo Bernardez, Marco Montagna, Nina Miolane, Lev Telyatnikov, "HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations." arXiv preprint arXiv:2505.15405, 2025.
Lev Telyatnikov, Guillermo Bernardez, Marco Montagna, Mustafa Hajij, Martin Carrasco, Pavlo Vasylenko, Mathilde Papillon, Ghada Zamzmi, Michael Schaub, Jonas Verhellen, ... others, "Topobench: A framework for benchmarking topological deep learning." arXiv preprint arXiv:2406.06642, 2024.
M. Palma, J. Gonzalez, M. Carrasco, R. Rubio-Noriega, K. Bergman, R. Azevedo, "Inter-Node Message Passing Through Optical Reconfigurable Memory Channel." IEEE Access, 2024.
G. Bernardez, L. Telyatnikov, M. Hajij, M. Carrasco, "ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain." In the proceedings of Geometric-Grounded Representation Learning and Generative Modelling at ICML 2024, 2024.
M. Carrasco, A. Berentzen, A. Garcia, "Applications of TopoX to Topological Deep Learning." In the proceedings of Geometric-Grounded Representation Learning and Generative Modelling at ICML 2024, 2024.
Poster at EDS2025, Warsaw, Poland
Poster at EEML, Sarajevo, Bosnia & Herzegovina
Poster at , Amsterdam, Netherlands
Poster at , Viena, Austria
Officially graduated from the M.Sc. in AI with a thesis grade of 9.5/10! Had a lot of fun reading about graph theory along the way, I am sad it’s over but I will be sharing the results soon enough!
It was fantastic to finall hear about AI regulation at EDS 2025, the talks by Prof. Petri and Prof. Petri where particularly interesting.
Best summer school of the season, definitly will do an EEML again. My favourite talk was on natural gradients by James Marten. Very cool topic!
What a big set of experts! This school showed me that probability is very cool, even cooler no-one is looking at the geometry!
Had the fantastic opportunity to attend LOGML - 2025 and work on Rademacher complexity bounds for GNNs. We will be realising more soon…