publications

A bit of my work

2026

  1. No Triangulation Without Representation: Generalization in Topological Deep Learning
    Johannes S Schmidt, Martin Carrasco, Ernst Röell, Guy Wolf, Nello Blaser, and 1 more author
    arXiv preprint arXiv:2605.06467, 2026
  2. Diversity Curves for Graph Representation Learning
    Katharina Limbeck, Nadja Häusermann, Martin Carrasco, Guy Wolf, and Bastian Rieck
    arXiv preprint arXiv:2605.06466, 2026
  3. Graph Homomorphism Distortion: A Metric to Distinguish Them All and in the Latent Space Bind Them
    Martin Carrasco, Olga Zaghen, Kavir Sumaraj, Erik Bekkers, and Bastian Rieck
    arXiv preprint arXiv:2511.03068, 2026
  4. On the Rademacher Complexity of GNNs: Unifying Expressivity and Geometry
    Martin Carrasco, Vahan A. Martirosyan, Aneeqa Mehrab, Caio Netto, Ehimare Okoyomon, and 1 more author
    Preprint, 2026

2025

  1. TopoBench: A Framework for Benchmarking Topological Deep Learning
    Lev Telyatnikov, Guillermo Bernardez, Marco Montagna, Mustafa Hajij, Martin Carrasco, and 32 more authors
    Journal of Data-centric Machine Learning Research, 2025
  2. HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations
    Guillermo Bernardez, Marco Montagna, Louis Van Langendonck, Martin Carrasco, Amirreza Akbari, and 5 more authors
    arXiv preprint arXiv:2505.15405, 2025
  3. Rademacher Meets Colors: More Expressivity, but at What Cost?
    Martin Carrasco, Vahan A. Martirosyan, Aneeqa Mehrab, Caio Netto, Ehimare Okoyomon, and 1 more author
    New Perspectives in Graph Machine Learning, 2025

2024

  1. Inter-node Message Passing through Optical Reconfigurable Memory Channel
    Mauricio G. Palma, Jorge Gonzalez, Martin Carrasco, Ruth Rubio-Noriega, Keren Bergman, and 1 more author
    IEEE Access, 2024
  2. Applications of TopoX to Equivariant Topological Networks
    Martin Carrasco, Andreas Berentzen, and Alejandro Garcia
    Jul 2024
    Code
  3. ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
    Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, and 68 more authors
    Proceedings of Machine Learning Research, Jul 2024
    PDF