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Jong-June Jeon
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2020 – today
- 2025
- [j8]Soyoung Cho
, Sungchul Hong
Adaptive adversarial augmentation for molecular property prediction. Expert Syst. Appl. 270: 126512 (2025) - [c5]Seunghwan An, Gyeongdong Woo, Jaesung Lim, ChangHyun Kim, Sungchul Hong, Jong-June Jeon:
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis. AAAI 2025: 15356-15364 - [i12]Mose Park, Yunjin Choi, Jong-June Jeon:
Does a Large Language Model Really Speak in Human-Like Language? CoRR abs/2501.01273 (2025) - 2024
- [j7]Seunghwan An
Customization of latent space in semi-supervised Variational AutoEncoder. Pattern Recognit. Lett. 177: 54-60 (2024) - [c4]Sungchul Hong
Cryptocurrency Price Forecasting using Variational Autoencoder with Versatile Quantile Modeling. CIKM 2024: 4530-4537 - [i11]Jaesung Park, Sungchul Hong, Yoonseo Cho, Jong-June Jeon:
Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations. CoRR abs/2405.03929 (2024) - [i10]Sungchul Hong, Seunghwan An, Jong-June Jeon:
Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering. CoRR abs/2405.19757 (2024) - [i9]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
- [j6]Minje Park, Jaeseon Kim, Sungchul Shin, Cheolwoo Park, Jong-June Jeon, Soon-Sun Kwon, Hosik Choi
Quantile estimation for encrypted data. Appl. Intell. 53(21): 24782-24791 (2023) - [c3]Seunghwan An, Kyungwoo Song, Jong-June Jeon:
Causally Disentangled Generative Variational AutoEncoder. ECAI 2023: 93-100 - [c2]Seunghwan An, Jong-June Jeon:
Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation. NeurIPS 2023 - [c1]Changdae Oh, Junhyuk So, Hoyoon Byun, YongTaek Lim, Minchul Shin, Jong-June Jeon, Kyungwoo Song:
Geodesic Multi-Modal Mixup for Robust Fine-Tuning. NeurIPS 2023 - [i8]Seunghwan An, Jong-June Jeon:
Distributional Variational AutoEncoder To Infinite Quantiles and Beyond Gaussianity. CoRR abs/2302.11294 (2023) - [i7]Seunghwan An, Kyungwoo Song, Jong-June Jeon:
Causally Disentangled Generative Variational AutoEncoder. CoRR abs/2302.11737 (2023) - [i6]Sungchul Hong, Yunjin Choi, Jong-June Jeon:
Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms. CoRR abs/2303.00515 (2023) - [i5]Sungchul Hong, Jong-June Jeon:
Uniform Pessimistic Risk and Optimal Portfolio. CoRR abs/2303.07158 (2023) - [i4]Seunghwan An, Jong-June Jeon:
Joint Distributional Learning via Cramer-Wold Distance. CoRR abs/2310.16374 (2023) - [i3]Seunghwan An, Sungchul Hong, Jong-June Jeon:
Balanced Marginal and Joint Distributional Learning via Mixture Cramer-Wold Distance. CoRR abs/2312.03307 (2023) - 2021
- [j5]Sang Jun Moon, Jong-June Jeon
Learning Multiple Quantiles With Neural Networks. J. Comput. Graph. Stat. 30(4): 1238-1248 (2021) - [j4]Gunwoong Park, Sang Jun Moon, Sion Park, Jong-June Jeon:
Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression. J. Mach. Learn. Res. 22: 102:1-102:41 (2021) - [i2]Seunghwan An, Hosik Choi, Jong-June Jeon:
EXoN: EXplainable encoder Network. CoRR abs/2105.10867 (2021) - 2020
- [j3]Jong-June Jeon
Primal path algorithm for compositional data analysis. Comput. Stat. Data Anal. 148: 106958 (2020)
2010 – 2019
- 2018
- [j2]Jong-June Jeon, Hosik Choi:
The sparse Luce model. Appl. Intell. 48(8): 1953-1964 (2018) - [i1]Jong-June Jeon, Yongdai Kim, Sungho Won, Hosik Choi:
Primal path algorithm for compositional data analysis. CoRR abs/1812.08954 (2018) - 2017
- [j1]Jong-June Jeon
Homogeneity detection for the high-dimensional generalized linear model. Comput. Stat. Data Anal. 114: 61-74 (2017)
Coauthor Index
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