A brief introduction of machine learning and its applications in high energy physics

by 昊 ZHANG (Institute of High Energy Physics, Chinese Academy of Sciences)

Tuesday 10 Apr 2018, 10:30 → 11:30 Asia/Shanghai

B105 (CHEP)

This is a review talk. In this talk, I will give a brief introduction of machine learning (ML) and its applications in high energy physics (HEP). After reviewing some basic conceptions, I would like to show some typical algorithms (CNN, RNN) and their applications in HEP appears in literatures. Unsupervised machine learning is a very interesting topic in ML. Some simple models such as Boltzmann machine and Generative Adversarial Networks (GAN) will be shown. An example of the application of GAN will be introduced very briefly.