Understanding and Improving Virtual Adversarial Training. - Dongha Kim; Yongchan Choi; Yongdai Kim (CoRR, 2019)

INN: A Method Identifying Clean-annotated Samples via Consistency Effect in Deep Neural Networks. - Dongha Kim; Yongchan Choi; Kunwoong Kim; Yongdai Kim (CoRR, 2021)

Experimental and Computational Study on the Ground Forces CGF Automation of Wargame Models Using Reinforcement Learning. - Minwoo Choi; Hoseok Moon; Sangwoo Han; Yongchan Choi; Minho Lee; Namsuk Cho (IEEE Access, 2022)

IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. - Dongha Kim; Yongchan Choi; Kunwoong Kim; Ilsang Ohn; Yongdai Kim (AAAI, 2024)

META-ANOVA: Screening interactions for interpretable machine learning. - Yongchan Choi; Seokhun Park; Chanmoo Park; Dongha Kim; Yongdai Kim (CoRR, 2024)

Tensor Product Neural Networks for Functional ANOVA Model. - Seokhun Park; Insung Kong; Yongchan Choi; Chanmoo Park; Yongdai Kim (CoRR, 2025)