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ORCIDDavid John Gagne II
Person information
- affiliation: National Center for Atmospheric Research, Boulder, CO, USA
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Journal Articles
- 2023
[j3]John S. Schreck
, William Petzke, Pedro A. Jimenez, Thomas Brummet, Jason C. Knievel, Eric James, Branko Kosovic, David John Gagne:
Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management. Remote. Sens. 15(13): 3372 (2023)- 2014
- [j2]Amy McGovern, David John Gagne II, John K. Williams, Rodger A. Brown, Jeffrey B. Basara:
Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning. Mach. Learn. 95(1): 27-50 (2014) - 2011
- [j1]Amy McGovern, David John Gagne II, Nathaniel Troutman, Rodger A. Brown, Jeffrey B. Basara, John K. Williams:
Using spatiotemporal relational random forests to improve our understanding of severe weather processes. Stat. Anal. Data Min. 4(4): 407-429 (2011)
Conference and Workshop Papers
- 2015
- [c5]David John Gagne II, Amy McGovern, Jerald Brotzge, Michael Coniglio, James Correia Jr., Ming Xue:
Day-Ahead Hail Prediction Integrating Machine Learning with Storm-Scale Numerical Weather Models. AAAI 2015: 3954-3960 - 2013
- [c4]David John Gagne II, Amy McGovern, Jerald Brotzge, Ming Xue:
Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework. ICDM Workshops 2013: 994-1001 - 2012
- [c3]David John Gagne II, Amy McGovern, Ming Xue:
Machine learning enhancement of Storm Scale Ensemble precipitation forecasts. CIDU 2012: 39-46 - 2010
- [c2]Amy McGovern, Timothy A. Supinie, David John Gagne II, Nathaniel Troutman, Matthew W. Collier, Rodger A. Brown, Jeffrey B. Basara, John K. Williams:
Severe Weather Processes through Spatiotemporal Relational Random Forests. CIDU 2010: 213-227 - 2008
- [c1]Amy McGovern, Nathan C. Hiers, Matthew W. Collier, David John Gagne II, Rodger A. Brown:
Spatiotemporal Relational Probability Trees: An Introduction. ICDM 2008: 935-940
Informal and Other Publications
- 2023
- [i8]John S. Schreck, Matthew Hayman, Gabrielle Gantos, Aaron Bansemer, David John Gagne:
Mimicking non-ideal instrument behavior for hologram processing using neural style translation. CoRR abs/2301.02757 (2023) - [i7]John S. Schreck, William Petzke, Pedro A. Jimenez, Thomas Brummet, Jason C. Knievel, Eric James, Branko Kosovic, David John Gagne:
Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management. CoRR abs/2305.11910 (2023) - [i6]John S. Schreck, David John Gagne II, Charlie Becker, William E. Chapman, Kim Elmore, Gabrielle Gantos, Eliot Kim, Dhamma Kimpara, Thomas Martin, Maria J. Molina, Vanessa M. Pryzbylo, Jacob Radford, Belen Saavedra, Justin Willson, Christopher D. Wirz:
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications. CoRR abs/2309.13207 (2023) - [i5]Yingkai Sha, Ryan A. Sobash, David John Gagne II:
Generative ensemble deep learning severe weather prediction from a deterministic convection-allowing model. CoRR abs/2310.06045 (2023) - [i4]Da Fan, Steven J. Greybush, David John Gagne II, Eugene E. Clothiaux:
Physically Explainable Deep Learning for Convective Initiation Nowcasting Using GOES-16 Satellite Observations. CoRR abs/2310.16015 (2023) - 2022
- [i3]John S. Schreck, Gabrielle Gantos, Matthew Hayman, Aaron Bansemer, David John Gagne:
Neural network processing of holographic images. CoRR abs/2203.08898 (2022) - 2021
- [i2]Amy McGovern, Imme Ebert-Uphoff, David John Gagne II, Ann Bostrom:
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences. CoRR abs/2112.08453 (2021) - 2019
- [i1]David John Gagne II, Hannah M. Christensen, Aneesh C. Subramanian, Adam H. Monahan:
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model. CoRR abs/1909.04711 (2019)
Coauthor Index
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