Self-Supervised Visual Representation Learning via Residual Momentum. - Trung X. Pham; Axi Niu; Kang Zhang 008; Sultan Rizky Hikmawan Madjid; Ji Woo Hong; Daehyeok Kim; Joshua Tian Jin Tee; Chang D. Yoo (CoRR, 2022)

ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure. - Hee Suk Yoon; Joshua Tian Jin Tee; Eunseop Yoon; Sunjae Yoon; Gwangsu Kim; Yingzhen Li; Chang D. Yoo (ICLR, 2023)

Self-Supervised Visual Representation Learning via Residual Momentum. - Trung Xuan Pham; Axi Niu; Kang Zhang 008; Joshua Tian Jin Tee; Ji Woo Hong; Chang D. Yoo (IEEE Access, 2023)

DifAugGAN: A Practical Diffusion-style Data Augmentation for GAN-based Single Image Super-resolution. - Axi Niu; Kang Zhang 008; Joshua Tian Jin Tee; Trung X. Pham; Jinqiu Sun; Chang D. Yoo; In So Kweon; Yanning Zhang 001 (CoRR, 2023)

BI-MDRG: Bridging Image History in Multimodal Dialogue Response Generation. - Hee Suk Yoon; Eunseop Yoon; Joshua Tian Jin Tee; Kang Zhang 008; Yu-Jung Heo; Du-Seong Chang; Chang D. Yoo (ECCV (31), 2024)

C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion. - Hee Suk Yoon; Eunseop Yoon; Joshua Tian Jin Tee; Mark A. Hasegawa-Johnson; Yingzhen Li; Chang D. Yoo (ICLR, 2024)

Physics Informed Distillation for Diffusion Models. - Joshua Tian Jin Tee; Kang Zhang 008; Hee Suk Yoon; Dhananjaya N. Gowda; Chanwoo Kim 001; Chang D. Yoo (Trans. Mach. Learn. Res., 2024)