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model interpretability
Explainability and Efficiency in Spatio-Temporal Models: Applications to Traffic Forecasting
Xiaochuan Gou, Ph.D. Student, Computer Science
Jul 6, 15:00
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18:00
B5 L5 R5209
traffic forecasting
Graph Neural Networks
model interpretability
This dissertation addresses key challenges in deep learning-based traffic forecasting, including computational efficiency, model interpretability, and data limitations, despite recent progress in spatio-temporal modeling techniques.
