Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples. - Sungyoon Lee; Woojin Lee; Jinseong Park 001; Jaewook Lee 001 (NeurIPS, 2021)

Comment on Transferability and Input Transformation with Additive Noise. - Hoki Kim; Jinseong Park 001; Jaewook Lee 001 (CoRR, 2022)

Differentially Private Sharpness-Aware Training. - Jinseong Park 001; Hoki Kim; Yujin Choi; Jaewook Lee 001 (ICML, 2023)

Implicit Jacobian regularization weighted with impurity of probability output. - Sungyoon Lee; Jinseong Park 001; Jaewook Lee 001 (ICML, 2023)

Fantastic Robustness Measures: The Secrets of Robust Generalization. - Hoki Kim; Jinseong Park 001; Yujin Choi; Jaewook Lee 001 (NeurIPS, 2023)

Exploring Diverse Feature Extractions for Adversarial Audio Detection. - Yujin Choi; Jinseong Park 001; Jaewook Lee 001; Hoki Kim (IEEE Access, 2023)

Stability Analysis of Sharpness-Aware Minimization. - Hoki Kim; Jinseong Park 001; Yujin Choi; Jaewook Lee 001 (CoRR, 2023)

Exploring the Effect of Multi-step Ascent in Sharpness-Aware Minimization. - Hoki Kim; Jinseong Park 001; Yujin Choi; Woojin Lee; Jaewook Lee 001 (CoRR, 2023)

Efficient differentially private kernel support vector classifier for multi-class classification. - Jinseong Park 001; Yujin Choi; Junyoung Byun; Jaewook Lee 001; Saerom Park (Inf. Sci., 2023)

Generating Transferable Adversarial Examples for Speech Classification. - Hoki Kim; Jinseong Park 001; Jaewook Lee 001 (Pattern Recognit., 2023)

Fast sharpness-aware training for periodic time series classification and forecasting. - Jinseong Park 001; Hoki Kim; Yujin Choi; Woojin Lee; Jaewook Lee 001 (Appl. Soft Comput., 2023)

Fair Sampling in Diffusion Models through Switching Mechanism. - Yujin Choi; Jinseong Park 001; Hoki Kim; Jaewook Lee 001; Saerom Park (AAAI, 2024)

In-Distribution Public Data Synthesis With Diffusion Models for Differentially Private Image Classification. - Jinseong Park 001; Yujin Choi; Jaewook Lee 001 (CVPR, 2024)

Are Self-Attentions Effective for Time Series Forecasting? - Dongbin Kim; Jinseong Park 001; Jaewook Lee 001; Hoki Kim (NeurIPS, 2024)

Fair Sampling in Diffusion Models through Switching Mechanism. - Yujin Choi; Jinseong Park 001; Hoki Kim; Jaewook Lee 001; Saeroom Park (CoRR, 2024)

Leveraging Priors via Diffusion Bridge for Time Series Generation. - Jinseong Park 001; Seungyun Lee; Woojin Jeong; Yujin Choi; Jaewook Lee 001 (CoRR, 2024)

BayesNAM: Leveraging Inconsistency for Reliable Explanations. - Hoki Kim; Jinseong Park 001; Yujin Choi; Seungyun Lee; Jaewook Lee 001 (CoRR, 2024)

Leveraging Programmatically Generated Synthetic Data for Differentially Private Diffusion Training. - Yujin Choi; Jinseong Park 001; Junyoung Byun; Jaewook Lee 001 (CoRR, 2024)

Safeguarding Privacy of Retrieval Data against Membership Inference Attacks: Is This Query Too Close to Home? - Yujin Choi; Youngjoo Park; Junyoung Byun; Jaewook Lee 001; Jinseong Park 001 (CoRR, 2025)