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ORCIDSeunghwan An
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- affiliation: Incheon National University, Republic of Korea
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2020 – today
- 2024
[j1]Seunghwan An
, Jong-June Jeon:
Customization of latent space in semi-supervised Variational AutoEncoder. Pattern Recognit. Lett. 177: 54-60 (2024)- [c3]Sungchul Hong, Seunghwan An, Jong-June Jeon:
Cryptocurrency Price Forecasting using Variational Autoencoder with Versatile Quantile Modeling. CIKM 2024: 4530-4537 - [i7]Sungchul Hong, Seunghwan An, Jong-June Jeon:
Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering. CoRR abs/2405.19757 (2024) - [i6]Seunghwan An, Gyeongdong Woo, Jaesung Lim, ChangHyun Kim, Sungchul Hong, Jong-June Jeon:
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis. CoRR abs/2405.20602 (2024) - 2023
- [c2]Seunghwan An, Kyungwoo Song, Jong-June Jeon:
Causally Disentangled Generative Variational AutoEncoder. ECAI 2023: 93-100 - [c1]Seunghwan An, Jong-June Jeon:
Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation. NeurIPS 2023 - [i5]Seunghwan An, Jong-June Jeon:
Distributional Variational AutoEncoder To Infinite Quantiles and Beyond Gaussianity. CoRR abs/2302.11294 (2023) - [i4]Seunghwan An, Kyungwoo Song, Jong-June Jeon:
Causally Disentangled Generative Variational AutoEncoder. CoRR abs/2302.11737 (2023) - [i3]Seunghwan An, Jong-June Jeon:
Joint Distributional Learning via Cramer-Wold Distance. CoRR abs/2310.16374 (2023) - [i2]Seunghwan An, Sungchul Hong, Jong-June Jeon:
Balanced Marginal and Joint Distributional Learning via Mixture Cramer-Wold Distance. CoRR abs/2312.03307 (2023) - 2021
- [i1]Seunghwan An, Hosik Choi, Jong-June Jeon:
EXoN: EXplainable encoder Network. CoRR abs/2105.10867 (2021)
Coauthor Index
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