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cs.LG2026
Interpretable Machine Learning for Traffic Congestion Prediction: Unveiling the Impact of Different COVID-19 Periods
Dan Zhu, Chi Sin Ng, Litian Xie +1
Traffic congestion prediction is essential for congestion mitigation, but the COVID-19 pandemic and related control measures altered travel behavior and increased prediction comple…
cs.LG2024
A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data
Yifan Wu, Yang Liu, Yue Yang +10
Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning of…