6 citations · 7 across the 5 of their papers we have counts for
5 papers
Uniform Pessimistic Risk and its Optimal Portfolio
Sungchul Hong, Jong-June Jeon
The optimal allocation of assets has been widely discussed with the theoretical analysis of risk measures, and pessimism is one of the most attractive approaches beyond the convent…
Causally Disentangled Generative Variational AutoEncoder
Seunghwan An, Kyungwoo Song, Jong-June Jeon
We present a new supervised learning technique for the Variational AutoEncoder (VAE) that allows it to learn a causally disentangled representation and generate causally disentangl…
Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation
Seunghwan An, Jong-June Jeon
The Gaussianity assumption has been consistently criticized as a main limitation of the Variational Autoencoder (VAE) despite its efficiency in computational modeling. In this pape…
EXoN: EXplainable encoder Network
SeungHwan An, Hosik Choi, Jong-June Jeon
We propose a new semi-supervised learning method of Variational AutoEncoder (VAE) which yields a customized and explainable latent space by EXplainable encoder Network (EXoN). Cust…
Primal path algorithm for compositional data analysis
Jong-June Jeon, Yongdai Kim, Sungho Won +1
Compositional data have two unique characteristics compared to typical multivariate data: the observed values are nonnegative and their summand is exactly one. To reflect these cha…