3 papers
stat.ML2026
Improving the sharpness in neural network-based parametric post-processing of ensemble forecasts
Ãgnes 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.AP2025
Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods
Martin János Mayer, Ãgnes Baran, Sebastian Lerch +3
Accurate and reliable forecasting of photovoltaic (PV) power generation is crucial for grid operations, electricity markets, and energy planning, as solar systems now contribute a…
stat.AP2024
Parametric model for post-processing visibility ensemble forecasts
Ãgnes Baran, Sándor Baran
Although by now the ensemble-based probabilistic forecasting is the most advanced approach to weather prediction, ensemble forecasts still might suffer from lack of calibration and…