no code implementations • 1 Aug 2023 • Seongsik Park, Jeonghee Jo, Jongkil Park, YeonJoo Jeong, Jaewook Kim, Suyoun Lee, Joon Young Kwak, Inho Kim, Jong-Keuk Park, Kyeong Seok Lee, Gye Weon Hwang, Hyun Jae Jang
Deep spiking neural networks (SNNs) are promising neural networks for their model capacity from deep neural network architecture and energy efficiency from SNNs' operations.
no code implementations • 1 Mar 2021 • Lei Ding, Xianghan Xu, Harald O. Jeschke, Xiaojian Bai, Erxi Feng, Admasu Solomon Alemayehu, Jaewook Kim, Feiting Huang, Qiang Zhang, Xiaxin Ding, Neil Harrison, Vivien Zapf, Daniel Khomskii, Igor I. Mazin, Sang-Wook Cheong, Huibo Cao
A toroidal dipole moment appears independent of the electric and magnetic dipole moment in the multipole expansion of electrodynamics.
Strongly Correlated Electrons Materials Science
no code implementations • 7 Nov 2019 • Semin Joung, Jaewook Kim, Sehyun Kwak, J. G. Bak, S. G. Lee, H. S. Han, H. S. Kim, Geunho Lee, Daeho Kwon, Y. -c. Ghim
A neural network solving Grad-Shafranov equation constrained with measured magnetic signals to reconstruct magnetic equilibria in real time is developed.
no code implementations • 23 Nov 2017 • Guhyun Kim, Vladimir Kornijcuk, Dohun Kim, Inho Kim, Jaewook Kim, Hyo Cheon Woo, Ji Hun Kim, Cheol Seong Hwang, Doo Seok Jeong
In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due in part to computational complexity in parameter optimization.