91 citations · 236 across the 31 of their papers we have counts for
6 papers · 1 filter
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi +1
Modeling non-Euclidean data is drawing extensive attention along with the unprecedented successes of deep neural networks in diverse fields. Particularly, a symmetric positive defi…
Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model
Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk
Existing studies on disease diagnostic models focus either on diagnostic model learning for performance improvement or on the visual explanation of a trained diagnostic model. We p…
Deep Joint Learning of Pathological Region Localization and Alzheimer's Disease Diagnosis
Changhyun Park, Heung-Il Suk
The identification of Alzheimer's disease (AD) and its early stages using structural magnetic resonance imaging (MRI) has been attracting the attention of researchers. Various data…
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis
Eunji Jun, Seungwoo Jeong, Da-Woon Heo +1
Transfer learning has gained attention in medical image analysis due to limited annotated 3D medical datasets for training data-driven deep learning models in the real world. Exist…
Fine-Grained Attention for Weakly Supervised Object Localization
Junghyo Sohn, Eunjin Jeon, Wonsik Jung +2
Although recent advances in deep learning accelerated an improvement in a weakly supervised object localization (WSOL) task, there are still challenges to identify the entire body…
Multi-view Integration Learning for Irregularly-sampled Clinical Time Series
Yurim Lee, Eunji Jun, Heung-Il Suk
Electronic health record (EHR) data is sparse and irregular as it is recorded at irregular time intervals, and different clinical variables are measured at each observation point.…