no code implementations • 12 Jun 2022 • Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Dae Sin Kim, Kee-Eung Kim, Changwook Jeong
Inductive transfer learning aims to learn from a small amount of training data for the target task by utilizing a pre-trained model from the source task.
no code implementations • 19 Apr 2022 • Sanghoon Myung, Wonik Jang, Seonghoon Jin, Jae Myung Choe, Changwook Jeong, Dae Sin Kim
Traditional TCAD simulation has succeeded in predicting and optimizing the device performance; however, it still faces a massive challenge - a high computational cost.
no code implementations • 6 Apr 2021 • Sanghoon Myung, Hyunjae Jang, Byungseon Choi, Jisu Ryu, Hyuk Kim, Sang Wuk Park, Changwook Jeong, Dae Sin Kim
The etching process is one of the most important processes in semiconductor manufacturing.
no code implementations • NeurIPS 2021 • Dae Young Park, Moon-Hyun Cha, Changwook Jeong, Dae Sin Kim, Bohyung Han
In other words, at the time of optimizing a teacher model, the proposed algorithm learns the student branches jointly to obtain student-friendly representations.