activity
20222024
most citedProbabilistic Imputation for Time-series Classification with Missing Data

5 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024

Fast Ensembling with Diffusion Schrödinger Bridge

Hyunsu Kim, Jongmin Yoon, Juho Lee

Deep Ensemble (DE) approach is a straightforward technique used to enhance the performance of deep neural networks by training them from different initial points, converging toward…

cs.CV2023

Sequential Data Generation with Groupwise Diffusion Process

Sangyun Lee, Gayoung Lee, Hyunsu Kim +2

We present the Groupwise Diffusion Model (GDM), which divides data into multiple groups and diffuses one group at one time interval in the forward diffusion process. GDM generates…

cs.LG20235 cited

Probabilistic Imputation for Time-series Classification with Missing Data

SeungHyun Kim, Hyunsu Kim, EungGu Yun +3

Multivariate time series data for real-world applications typically contain a significant amount of missing values. The dominant approach for classification with such missing value…

cs.CV20231 cited

User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques

Sunwoo Kim, Wooseok Jang, Hyunsu Kim +4

Recent text-driven image editing in diffusion models has shown remarkable success. However, the existing methods assume that the user's description sufficiently grounds the context…

cs.LG2023

Regularizing Towards Soft Equivariance Under Mixed Symmetries

Hyunsu Kim, Hyungi Lee, Hongseok Yang +1

Datasets often have their intrinsic symmetries, and particular deep-learning models called equivariant or invariant models have been developed to exploit these symmetries. However,…

cs.CV2023

Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization

Doyeon Kim, Eunji Ko, Hyunsu Kim +5

Portrait stylization, which translates a real human face image into an artistically stylized image, has attracted considerable interest and many prior works have shown impressive q…