2 papers
cs.LG2025
A Probabilistic U-Net Approach to Downscaling Climate Simulations
Maryam Alipourhajiagha, Pierre-Louis Lemaire, Youssef Diouane +1
Climate models are limited by heavy computational costs, often producing outputs at coarse spatial resolutions, while many climate change impact studies require finer scales. Stati…
cs.LG2024
Interpolation-Free Deep Learning for Meteorological Downscaling on Unaligned Grids Across Multiple Domains with Application to Wind Power
Jean-Sébastien Giroux, Simon-Philippe Breton, Julie Carreau
As climate change intensifies, the shift to cleaner energy sources becomes increasingly urgent. With wind energy production set to accelerate, reliable wind probabilistic forecasts…