87 citations · 148 across the 20 of their papers we have counts for
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stat.ME2023★ 1 cited
Data-driven uncertainty quantification for constrained stochastic differential equations and application to solar photovoltaic power forecast data
Khaoula Ben Chaabane, Ahmed Kebaier, Marco Scavino +1
In this work, we extend the data-driven Itô stochastic differential equation (SDE) framework for the pathwise assessment of short-term forecast errors to account for the time-depen…
stat.ME2020★ 8 cited
Quantifying Uncertainty with a Derivative Tracking SDE Model and Application to Wind Power Forecast Data
Renzo Caballero, Ahmed Kebaier, Marco Scavino +1
We develop a data-driven methodology based on parametric Itô's Stochastic Differential Equations (SDEs) to capture the real asymmetric dynamics of forecast errors. Our SDE framewor…