Machine Learning for high energy nuclear physics
Speaker: Pang Long-Gang (CCNU)
Time: Nov. 24 (Tuesday) 9:00am (New York), 6:00am (San Fransisco), 3:00pm (Frankfurt) 7:30pm(New Delhi), 10:00pm (Beijing), 11:00pm (Tokyo)
Abstract: Machine learning represents a collection of algorithms that let the computer learn patterns from data by themselves. These algorithms have been widely used in physics, to look for patterns that can disentangle different physics in the inverse problem of various processes. This talk will not only review the recent applications of machine learning for high energy nuclear physics, but also introduce several state-of-the-art machine learning tools used in particle and low energy nuclear physics. These advanced techniques may help us to tackle unsolved problems in high energy nuclear physics.
Chair: Xing-Bo Zhao
ZOOM link: Please register here, the ZOOM link will be send in the comming Monday by group email. By attending this event you agree to the seminar and discussion being recorded and posted on the seminar web site.
Materials:
Material link：https://pan.baidu.com/s/18Zn5Bpui9Ub7Wl69kEmXZw
passcode：phys
Onedrive link: https://1drv.ms/u/s!Ar4LrhZS__MAgicXsaDfiY00FeJN?e=eGhrmO
