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A Flexible Rolling Regression Framework for Time-Varying SIRD models: Application to COVID-19
The present paper introduces a data-driven framework for describing the time-varying nature of an SIRD model in the context of COVID-19.
Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants
Atmospheric modeling has recently experienced a surge with the advent of deep learning.
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