EXoN: EXplainable encoder Network. - Seunghwan An; Hosik Choi; Jong-June Jeon (CoRR, 2021)

Causally Disentangled Generative Variational AutoEncoder. - Seunghwan An; Kyungwoo Song; Jong-June Jeon (ECAI, 2023)

Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation. - Seunghwan An; Jong-June Jeon (NeurIPS, 2023)

Distributional Variational AutoEncoder To Infinite Quantiles and Beyond Gaussianity. - Seunghwan An; Jong-June Jeon (CoRR, 2023)

Joint Distributional Learning via Cramer-Wold Distance. - Seunghwan An; Jong-June Jeon (CoRR, 2023)

Balanced Marginal and Joint Distributional Learning via Mixture Cramer-Wold Distance. - Seunghwan An; Sungchul Hong; Jong-June Jeon (CoRR, 2023)

Cryptocurrency Price Forecasting using Variational Autoencoder with Versatile Quantile Modeling. - Sungchul Hong; Seunghwan An; Jong-June Jeon (CIKM, 2024)

Customization of latent space in semi-supervised Variational AutoEncoder. - Seunghwan An; Jong-June Jeon (Pattern Recognit. Lett., 2024)

Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis. - Seunghwan An; Gyeongdong Woo; Jaesung Lim 002; ChangHyun Kim; Sungchul Hong; Jong-June Jeon (AAAI, 2025)

Improving SMOTE via fusing conditional VAE for data-adaptive noise filtering. - Sungchul Hong; Seunghwan An; Jong-June Jeon (Appl. Intell., 2025)