35 citations · 65 across the 7 of their papers we have counts for
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stat.ML2026
Improving the sharpness in neural network-based parametric post-processing of ensemble forecasts
Ágnes Baran, Máté Mihalina
Statistical post-processing has proven to be an effective tool in improving ensemble forecast of different weather variables. Case studies show that post-processing can remedy the…
stat.ML2022★ 9 cited
A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
Ágnes Baran, Sándor Baran
By the end of 2021, the renewable energy share of the global electricity capacity reached 38.3% and the new installations are dominated by wind and solar energy, showing global inc…
stat.ML2020★ 35 cited
Machine learning for total cloud cover prediction
Ágnes Baran, Sebastian Lerch, Mehrez El Ayari +1
Accurate and reliable forecasting of total cloud cover (TCC) is vital for many areas such as astronomy, energy demand and production, or agriculture. Most meteorological centres is…