6 papers
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification
YongKyung Oh, Dong-Young Lim, Sungil Kim +1
Handling missing data in time series classification remains a significant challenge in various domains. Traditional methods often rely on imputation, which may introduce bias or fa…
Engagement Intensity as a Learner-Modeling Signal for Adaptive AI Ethics Instruction
Yongkyung Oh, Lynn Talton, Alex Bui
Adaptive AI ethics instruction in graduate research training benefits from intake measures that reflect differences in prior LLM experience. Prior coursework or workshop attendance…
Silent Failures in Federated Personalization of Foundation Models
YongKyung Oh, Alex Bui
Foundation models are increasingly personalized on decentralized private data through federated learning and are now deployed at scale under growing regulatory requirements for pos…
Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review
YongKyung Oh, Henry W. Zheng, Jeffrey Feng +1
Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore primary sampling units, stratifica…
Comprehensive Review of Neural Differential Equations for Time Series Analysis
YongKyung Oh, Seungsu Kam, Jonghun Lee +3
Time series modeling and analysis have become critical in various domains. Conventional methods such as RNNs and Transformers, while effective for discrete-time and regularly sampl…
Multi-View Contrastive Learning for Robust Domain Adaptation in Medical Time Series Analysis
YongKyung Oh, Alex Bui
Adapting machine learning models to medical time series across different domains remains a challenge due to complex temporal dependencies and dynamic distribution shifts. Current a…