Introduction to machine learning in high energy physics

• Gregor Kasieczka (Hamburg University (DE))

Graph neural networks

• Nikita Kazeev (Yandex School of Data Analysis (RU))

Generative Models and Where to Find Them in HEP

• Michael Aaron Kagan (SLAC National Accelerator Laboratory (US))

BDT, shallow and deep neural network techniques for analysis and detector reconstruction

• Gian Michele Innocenti (CERN)