Application of Deep Reinforcement Learning to Dynamic Verification of DRAM Designs. - Hyojin Choi; In Huh; Seungju Kim; Jeonghoon Ko; Changwook Jeong; Hyeonsik Son; Kiwon Kwon; Joonwan Chai; Younsik Park; Jaehoon Jeong; Daesin Kim; Jung Yun Choi (DAC, 2021)

Learning Student-Friendly Teacher Networks for Knowledge Distillation. - Dae Young Park; Moon-Hyun Cha; Changwook Jeong; Daesin Kim; Bohyung Han (NeurIPS, 2021)

A Novel Approach for Semiconductor Etching Process with Inductive Biases. - Sanghoon Myung; Hyunjae Jang; Byungseon Choi; Jisu Ryu; Hyuk Kim; Sang Wuk Park; Changwook Jeong; Daesin Kim (CoRR, 2021)

PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. - Sanghoon Myung; In Huh; Wonik Jang; Jae Myung Choe; Jisu Ryu; Daesin Kim; Kee-Eung Kim; Changwook Jeong (ICML, 2022)

Restructuring TCAD System: Teaching Traditional TCAD New Tricks. - Sanghoon Myung; Wonik Jang; Seonghoon Jin; Jae Myung Choe; Changwook Jeong; Daesin Kim (CoRR, 2022)

Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning. - In Huh; Changwook Jeong; Jae Myung Choe; Younggu Kim; Daesin Kim (NeurIPS, 2023)

Enhancement of In2O3 Field-Effect Mobility Up To 152 cm2.V-1·s-1Using HZO-Based Higher-k Linear Dielectric. - Zehao Lin; Chang Niu; Hyeongjun Jang; Taehyun Kim; Yizhi Zhang; Haiyan Wang; Changwook Jeong; Peide D. Ye (VLSI Technology and Circuits, 2024)