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GPPU Seminar

Machine learning and theoretical physics

Akio Tomiya
(International Professional University of Technology in Osaka)


Date

13:30-15:30, March 07th, 2024

Place

(hybrid) Room 745, Science Complex B (H-03), Zoom registration map

Abstract

In recent years, research on theoretical physics using machine learning has been actively conducted. This involves not only treating neural nets as black boxes, but also designing the structure of neural nets to match the physical system to be computed, and conversely, attempting to understand neural nets themselves using physics methods. In this lecture, we will summarize recent developments and introduce them to the interdisciplinary field called machine learning physics.

Point

GSP 1

Contact: Yusuke Tanimura (tanimura [at] nucl.phys.tohoku.ac.jp)