3 citations · 4 across the 4 of their papers we have counts for
4 papers
TabSODA: Tabular Diffusion based Imputation with Skip Pattern Detection and Ordinal Awareness
Yuyu Chen, Taehyo Kim, Hai Shu +1
Missing data imputation in large-scale surveys faces two challenges that are not well handled by current tabular diffusion methods. First, \emph{structural skips}, cells made inapp…
A False Discovery Rate Control Method Using a Fully Connected Hidden Markov Random Field for Neuroimaging Data
Taehyo Kim, Qiran Jia, Mony J. de Leon +1
False discovery rate (FDR) control methods are essential for voxel-wise multiple testing in neuroimaging data analysis, where hundreds of thousands or even millions of tests are co…
UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor Segmentation
Yanbing Chen, Tianze Tang, Taehyo Kim +1
Background: Gliomas are among the most common malignant brain tumors and exhibit substantial heterogeneity, complicating accurate detection and segmentation. Although multi-modal M…
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data
Taehyo Kim, Hai Shu, Qiran Jia +1
Voxel-based multiple testing is widely used in neuroimaging data analysis. Traditional false discovery rate (FDR) control methods often ignore the spatial dependence among the voxe…