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cs.LG2026
Domain Generalization under Sampling Pattern Shifts in Irregular Time Series
Changhun Kim, Joohyung Lee, Kwanhyung Lee +3
Irregularly sampled multivariate time series (ISMTS) are prevalent in real-world applications, where both observation times and available measurements can vary substantially across…
cs.LG2026
Learning to Select Source-Traceable Evidence for Language-Model Prediction from Irregular Clinical Time Series
Kwanhyung Lee, Juhwan Choi, Jongheon Kim +5
Numerical time-series models effectively process irregular electronic health record (EHR) trajectories, but do not expose which temporal patterns support each prediction as readabl…
cs.LG2026
Structure-Aware Set Transformers: Temporal and Variable-Type Attention Biases for Asynchronous Clinical Time Series
Joohyung Lee, Kwanhyung Lee, Changhun Kim +1
Electronic health records (EHR) are irregular, asynchronous multivariate time series. As time-series foundation models increasingly tokenize events rather than discretizing time, t…