26 citations · 27 across the 3 of their papers we have counts for
4 papers
Winter Precipitation Type Diagnosis and Uncertainty Quantification with a Physically Consistent Machine Learning Method
Charlie Becker, David John Gagne, Julie Demuth +8
Accurately forecasting winter precipitation type and its transitions is critical for high-impact decision making. However, existing methods struggle in thermodynamically ambiguous…
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications
John S. Schreck, David John Gagne, Charlie Becker +13
Robust quantification of predictive uncertainty is critical for understanding factors that drive weather and climate outcomes. Ensembles provide predictive uncertainty estimates an…
Mimicking non-ideal instrument behavior for hologram processing using neural style translation
John S. Schreck, Matthew Hayman, Gabrielle Gantos +2
Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can…
Neural network processing of holographic images
John S. Schreck, Gabrielle Gantos, Matthew Hayman +2
HOLODEC, an airborne cloud particle imager, captures holographic images of a fixed volume of cloud to characterize the types and sizes of cloud particles, such as water droplets an…