Advanced Artificial Intelligence for Precision High Energy Physics

Artificial intelligence techniques are becoming increasingly important in high energy physics (HEP), with a range of applications that goes from analytic computations to modeling and optimization. Many of these applications tackle cutting-edge problems in machine learning (ML), and in fact address issues, such as the need to accurate uncertainty estimations, that are often disregarded in the most common ML applications. The goal of this school is to provide hands-on training on cutting edge machine learning methods in HEP by combining extensive advanced courses taught with extended tutorial sessions. The tutorials will exploit as a playing ground the NNPDF open-source code, which, originally aimed at the determination of parton distribution, makes use of a variety of current ML, statistical and analysis tools and techniques of wide applicability.

The school is aimed at advanced PhD students and post-docs. Participants will be selected based on motivation and qualifications.

No registration fee is required. Lunches and a conference dinner will be provided for free to participants, however participants will have to arrange and pay for their accommodation and the other dinners. A number of rooms are available at the local guesthouse upon request at registration.

Registrations will last until March 31st, 2023.

The school is hosted by the Lake Como School of Advanced Studies and co-organized by Università degli studi di Milano (Italy), NIKHEF (The Netherlands), Vrije Universiteit Amsterdam (The Netherlands) and the Higgs Centre for Theoretical Physics, Edinburgh University (UK).