9 citations · 16 across the 9 of their papers we have counts for
4 papers · 1 filter
Estimating Subgraph Importance with Structural Prior Domain Knowledge
Changhyun Kim, Seunghwan An, Jong-June Jeon
We propose a subgraph importance estimation method for pretrained Graph Neural Networks (GNNs) on graph-level tasks, formulated as a linear Group Lasso regression problem in the em…
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
Seunghwan An, Gyeongdong Woo, Jaesung Lim +3
In this paper, our goal is to generate synthetic data for heterogeneous (mixed-type) tabular datasets with high machine learning utility (MLu). Since the MLu performance depends on…
Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering
Sungchul Hong, Seunghwan An, Jong-June Jeon
Recent advances in a generative neural network model extend the development of data augmentation methods. However, the augmentation methods based on the modern generative models fa…
Joint Distributional Learning via Cramer-Wold Distance
Seunghwan An, Jong-June Jeon
The assumption of conditional independence among observed variables, primarily used in the Variational Autoencoder (VAE) decoder modeling, has limitations when dealing with high-di…