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Showing 1–3 of 3 results
Advanced filters: Author: Gorka Muñoz-Gil Clear advanced filters

  • Muñoz-Gil and colleagues report the results of an open challenge where they benchmarked algorithms for the characterization of motion changes in single-particle tracking. By ranking methods on simulations, the competition revealed strengths and limitations of AI and classic approaches, guiding researchers toward optimal tools.

    • Gorka Muñoz-Gil
    • Harshith Bachimanchi
    • Carlo Manzo
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-17

  • Achieving the promised advantages of quantum computing relies on translating quantum operations into physical realizations. Fürrutter and colleagues use diffusion models to create quantum circuits that are based on user specifications and tailored to experimental constraints.

    • Florian Fürrutter
    • Gorka Muñoz-Gil
    • Hans J. Briegel
    Research
    Nature Machine Intelligence
    Volume: 6, P: 515-524

  • Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport dynamics but often difficult to characterize. Here the authors compare approaches for single trajectory analysis through an open competition, showing that machine learning methods outperform classical approaches.

    • Gorka Muñoz-Gil
    • Giovanni Volpe
    • Carlo Manzo
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-16