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David Gagne
NSF National Center for Atmospheric ResearchMeeting roles in:
Evaluating AI-Based Numerical Weather Prediction Models for Precipitation Type Classification Using Crowd-Sourced Observations
Scalable, Uncertainty-Aware Streamflow Prediction in Snow-Dominated Catchments Using Evidential Deep Learning and CLM5 Ensembles
Uncertainty Estimation and Explanation for Convective Initiation Nowcasting Using Bayesian Deep Learning
Exploring Structural Differences and Parameter Calibration for Microphysics in CESM with Latent Representations using Contrastive Learning Models
Deep Contrastive Learning for Microphysics Scheme Comparison in a Perturbed Initial Condition CESM Ensemble
Disentangled Contrastive Representation Learning for Interpretable Analysis of Warm Rain Microphysics Schemes
Applying the AI Weather Prediction Revolution to Regional Hydroclimate: Coupling, Scales, and Reliability
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