CopFITi is the first marginalization-consistent copula for irregular multivariate time series, using normalizing flows for marginals and a Gaussian mixture copula for dependencies to reach new state-of-the-art joint density modeling.
Multitask Gaus- sian processes for multivariate physiological time-series analysis
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An LLM-guided framework simulates physiological trajectories to provide interpretable early warnings for sepsis, achieving AUC scores of 0.861-0.903 on MIMIC-IV and eICU data.
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Valid and Expressive Copulas for Irregular Multivariate Time Series
CopFITi is the first marginalization-consistent copula for irregular multivariate time series, using normalizing flows for marginals and a Gaussian mixture copula for dependencies to reach new state-of-the-art joint density modeling.
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Clinically Interpretable Sepsis Early Warning via LLM-Guided Simulation of Temporal Physiological Dynamics
An LLM-guided framework simulates physiological trajectories to provide interpretable early warnings for sepsis, achieving AUC scores of 0.861-0.903 on MIMIC-IV and eICU data.