3 papers
cs.LG2025
Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed
Harrison J. Goldwyn, Mitchell Krock, Johann Rudi +2
Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While exis…
stat.ML2025
Enhancing Interpretability in Generative Modeling: Statistically Disentangled Latent Spaces Guided by Generative Factors in Scientific Datasets
Arkaprabha Ganguli, Nesar Ramachandra, Julie Bessac +1
This study addresses the challenge of statistically extracting generative factors from complex, high-dimensional datasets in unsupervised or semi-supervised settings. We investigat…
stat.AP2024
Joint modeling of wind speed and wind direction through a conditional approach
Eva Murphy, Whitney Huang, Julie Bessac +2
Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to cl…