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Attended LOGML 2025

Published: July 04, 2025

Had the fantastic opportunity to attend LOGML - 2025 and work on Rademacher complexity bounds for GNNs. We will be realising more soon…

Attended the Probabilistic ML School by ELLIS

Published: July 16, 2025

What a big set of experts! This school showed me that probability is very cool, even cooler no-one is looking at the geometry!

Attended EEML 2025

Published: July 24, 2025

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!

Attended EDS 2025

Published: August 30, 2025

It was fantastic to finall hear about AI regulation at EDS 2025, the talks by Prof. Petri and Prof. Petri where particularly interesting.

M.Sc. Graduation

Published: August 31, 2025

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!

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publications

Applications of TopoX to Topological Deep Learning

Published in In the proceedings of Geometric-Grounded Representation Learning and Generative Modelling at ICML 2024, 2024

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Recommended citation: 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.
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ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

Published in In the proceedings of Geometric-Grounded Representation Learning and Generative Modelling at ICML 2024, 2024

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Recommended citation: 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.

Inter-Node Message Passing Through Optical Reconfigurable Memory Channel

Published in IEEE Access, 2024

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Recommended citation: 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.

Topobench: A framework for benchmarking topological deep learning

Published in arXiv preprint arXiv:2406.06642, 2024

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Recommended citation: 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.

HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations

Published in arXiv preprint arXiv:2505.15405, 2025

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Recommended citation: 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.