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20242026
most citedWind Power Assessment based on Super-Resolution and Downscaling -- A Comparison of Deep Learning Methods

1 citations · 2 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2025

Forecast Skill Is Not Decision Skill: Evidence from Weather-Dependent Decision Tasks

Kornelius Raeth, Nicole Ludwig

Standard weather forecast evaluations focus on the forecaster's perspective and on a statistical assessment comparing forecasts and observations. In practice, however, forecasts ar…

cs.LG2025

Bounded Graph Clustering with Graph Neural Networks

Kibidi Neocosmos, Diego Baptista, Nicole Ludwig

In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible values is computationally infeasible…

eess.SY2025

Fault Detection in Solar Thermal Systems using Probabilistic Reconstructions

Florian Ebmeier, Nicole Ludwig, Jannik Thuemmel +2

Solar thermal systems (STS) present a promising avenue for low-carbon heat generation, with a well-running system providing heat at minimal cost and carbon emissions. However, STS…

cs.LG2025

Assessing the risk of future Dunkelflaute events for Germany using generative deep learning

Felix Strnad, Jonathan Schmidt, Fabian Mockert +2

The European electricity power grid is transitioning towards renewable energy sources, characterized by an increasing share of off- and onshore wind and solar power. However, the w…

cs.CV2025

RainShift: A Benchmark for Precipitation Downscaling Across Geographies

Paula Harder, Luca Schmidt, Francis Pelletier +5

Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is…