The use of new methods for processing data of a physical experiment. Application of machine learning methods on the NICA complex.

Generative models for particle physics: hype, profits, and pitfalls.

28 Aug 2023, 10:10

30m

Ether (St. Petersburg, Nevsky 1)

Speaker

Fedor Ratnikov (Yandex School of Data Analysis (RU))

Description

Generative ML models are widely used in the modern world to solve different practical problems. This approach is a very promising solution for various problems in experimental particle and nuclear physics. However, specific requirements of using such models for obtaining quantitative scientific results put restrictions on direct using industrial generative models out of the box.

This presentation will list main use cases of using generative models for experimental particle physics, discuss possible issues and specific requirements to such models, and demonstrate practical approaches to resolve those issues.

Presentation materials

GenforHEP_230828_SPB.pdf