CT-Former integrates continuous-time modeling and causal attention in a transformer to deliver accurate, interpretable early AKI prediction on the MIMIC-IV cohort of 18,419 patients.
An introduction to roc analysis
2 Pith papers cite this work. Polarity classification is still indexing.
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Von Mises ensemble yields angular uncertainty estimates that integrate directly into tracking via closed-form likelihoods and shows stronger perturbation sensitivity than evidential deep learning on radar DOA tasks.
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Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury
CT-Former integrates continuous-time modeling and causal attention in a transformer to deliver accurate, interpretable early AKI prediction on the MIMIC-IV cohort of 18,419 patients.
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Von Mises Based Uncertainty Quantification for Closely Spaced Automotive Radar Targets
Von Mises ensemble yields angular uncertainty estimates that integrate directly into tracking via closed-form likelihoods and shows stronger perturbation sensitivity than evidential deep learning on radar DOA tasks.