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Revision as of 13:05, 23 October 2018 by LeeMyeongwon (talk | contribs) (Created page with "thumb|x300px|Dr. Lee, Chang-Woo (KIAS) * Speaker: Dr. Lee, Chang-Woo (KIAS) * Date: Wednesday February 21, 2018 05:00pm * Place: Jungho...")
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Dr. Lee, Chang-Woo (KIAS)

Machine learning (ML) is now permeating into almost every field of science; physics seems to be no exception. Recently, many overseas groups are utilizing ML to attack hard-to-solve problems (mostly) in the context of many-body physics. Although concrete insight is still far from our grasp via this technique, ML often shows good performance beyond our expectation. Following the trend of using ML as a data-analyzing or feature-extracting tool for physics, this talk will briefly touch on the history, types, and background theories of ML; it will also browse through some recent studies in this line.