Speaker
Keun-Young Kim
(GIST)
Description
We utilize a deep learning approach to infer the bulk spacetime from boundary data, including optical conductivity and entanglement entropy. This method is particularly intriguing as it models AdS space using a deep neural network framework. Furthermore, our approach is universal, making it applicable to a wide range of physics problems that involve differential equations and integrals
