Machine learning in high energy physics: a conversation over ice cream

Contribution List

1. Introduction to machine learning in high energy physics

Gregor Kasieczka (Hamburg University (DE))

05/10/2021, 16:00

2. Graph neural networks

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

05/10/2021, 16:25

3. Generative Models and Where to Find Them in HEP

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

05/10/2021, 16:50

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

Gian Michele Innocenti (CERN)

05/10/2021, 17:15