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stat.AP2024
CESAR: A Convolutional Echo State AutoencodeR for High-Resolution Wind Forecasting
Matthew Bonas, Paolo Giani, Paola Crippa +1
An accurate and timely assessment of wind speed and energy output allows an efficient planning and management of this resource on the power grid. Wind energy, especially at high re…
stat.AP2023★ 1 cited
High Resolution Global Precipitation Downscaling with Latent Gaussian Models and Nonstationary SPDE Structure
Jiachen Zhang, Matthew Bonas, Diogo Bolster +2
Obtaining high-resolution maps of precipitation data can provide key insights to stakeholders to assess a sustainable access to water resources at urban scale. Mapping a nonstation…
stat.AP2021★ 1 cited
Calibration of Spatio-Temporal Forecasts from Citizen Science Urban Air Pollution Data with Sparse Recurrent Neural Networks
Matthew Bonas, Stefano Castruccio
With their continued increase in coverage and quality, data collected from personal air quality monitors has become an increasingly valuable tool to complement existing public heal…