The aim of the school is to present methodological, computational and machine learning methods for complex networks analysis, with applications spanning a wide range of fields.

The school will present a comprehensive view of the theoretical aspects of challenging topics in network theory, including higher order networks, diffusive models on networks, probabilistic and machine learning approaches, as well as computational methods. A wide range of applications will be explored during the lectures, including socio-economic and financial applications.

A Python tutorial held by lecturers/teaching assistants will follow the lecture to show the implementation of the methods studied during the theoretical class and the proposed application.

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