David John Gagne II
David John Gagne II
Adresă de e-mail confirmată pe ucar.edu
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Making the black box more transparent: Understanding the physical implications of machine learning
A McGovern, R Lagerquist, DJ Gagne, GE Jergensen, KL Elmore, ...
Bulletin of the American Meteorological Society 100 (11), 2175-2199, 2019
Using artificial intelligence to improve real-time decision-making for high-impact weather
A McGovern, KL Elmore, DJ Gagne, SE Haupt, CD Karstens, R Lagerquist, ...
Bulletin of the American Meteorological Society 98 (10), 2073-2090, 2017
Interpretable deep learning for spatial analysis of severe hailstorms
DJ Gagne II, SE Haupt, DW Nychka, G Thompson
Monthly Weather Review 147 (8), 2827-2845, 2019
Storm-based probabilistic hail forecasting with machine learning applied to convection-allowing ensembles
DJ Gagne, A McGovern, SE Haupt, RA Sobash, JK Williams, M Xue
Weather and forecasting 32 (5), 1819-1840, 2017
Machine learning for stochastic parameterization: Generative adversarial networks in the Lorenz'96 model
DJ Gagne, HM Christensen, AC Subramanian, AH Monahan
Journal of Advances in Modeling Earth Systems 12 (3), e2019MS001896, 2020
Deep learning for spatially explicit prediction of synoptic-scale fronts
R Lagerquist, A McGovern, DJ Gagne II
Weather and Forecasting 34 (4), 1137-1160, 2019
Deep learning on three-dimensional multiscale data for next-hour tornado prediction
R Lagerquist, A McGovern, CR Homeyer, DJ Gagne II, T Smith
Monthly Weather Review 148 (7), 2837-2861, 2020
Machine learning enhancement of storm-scale ensemble probabilistic quantitative precipitation forecasts
DJ Gagne, A McGovern, M Xue
Weather and Forecasting 29 (4), 1024-1043, 2014
Classification of convective areas using decision trees
DJ Gagne, A McGovern, J Brotzge
Journal of Atmospheric and Oceanic Technology 26 (7), 1341-1353, 2009
Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science
A McGovern, I Ebert-Uphoff, DJ Gagne, A Bostrom
Environmental Data Science 1, e6, 2022
Machine learning the warm rain process
A Gettelman, DJ Gagne, CC Chen, MW Christensen, ZJ Lebo, H Morrison, ...
Journal of Advances in Modeling Earth Systems 13 (2), e2020MS002268, 2021
Deep-learning-based gridded downscaling of surface meteorological variables in complex terrain. Part I: Daily maximum and minimum 2-m temperature
Y Sha, DJ Gagne II, G West, R Stull
Journal of Applied Meteorology and Climatology 59 (12), 2057-2073, 2020
Explicit forecasts of low-level rotation from convection-allowing models for next-day tornado prediction
RA Sobash, GS Romine, CS Schwartz, DJ Gagne, ML Weisman
Weather and Forecasting 31 (5), 1591-1614, 2016
Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning
A McGovern, DJ Gagne, JK Williams, RA Brown, JB Basara
Machine learning 95, 27-50, 2014
Calibration of machine learning–based probabilistic hail predictions for operational forecasting
A Burke, N Snook, DJ Gagne II, S McCorkle, A McGovern
Weather and Forecasting 35 (1), 149-168, 2020
Deep-learning-based gridded downscaling of surface meteorological variables in complex terrain. Part II: Daily precipitation
Y Sha, DJ Gagne II, G West, R Stull
Journal of Applied Meteorology and Climatology 59 (12), 2075-2092, 2020
Spatiotemporal relational probability trees: An introduction
A McGovern, NC Hiers, M Collier, DJ Gagne II, RA Brown
2008 Eighth IEEE International Conference on Data Mining, 935-940, 2008
Challenges and benchmark datasets for machine learning in the atmospheric sciences: Definition, status, and outlook
PD Dueben, MG Schultz, M Chantry, DJ Gagne, DM Hall, A McGovern
Artificial Intelligence for the Earth Systems 1 (3), e210002, 2022
Evaluation of statistical learning configurations for gridded solar irradiance forecasting
DJ Gagne II, A McGovern, SE Haupt, JK Williams
Solar Energy 150, 383-393, 2017
Solar energy prediction: An international contest to initiate interdisciplinary research on compelling meteorological problems
A McGovern, DJ Gagne, J Basara, TM Hamill, D Margolin
Bulletin of the American Meteorological Society 96 (8), 1388-1395, 2015
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