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AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography.
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- AI Magazine, 2024, v. 45, n. 1, p. 105, doi. 10.1002/aaai.12160
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Aggregation strategies to improve XAI for geoscience models that use correlated, high-dimensional rasters.
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- Environmental Data Science, 2023, v. 2, p. 1, doi. 10.1017/eds.2023.39
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- Article
A Deep Learning Based Method to Delineate the Wet/Dry Shoreline and Compute Its Elevation Using High-Resolution UAS Imagery.
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- Remote Sensing, 2022, v. 14, n. 23, p. 5990, doi. 10.3390/rs14235990
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- Article
Relative Importance of Large‐Scale Environmental Variables to the World‐Wide Variability of Thunderstorms.
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- Journal of Geophysical Research. Atmospheres, 2022, v. 127, n. 17, p. 1, doi. 10.1029/2021JD036065
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- Article
NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES).
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- Bulletin of the American Meteorological Society, 2022, v. 103, n. 7, p. E1658, doi. 10.1175/BAMS-D-21-0020.1
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- Article
An Approach to Approximate Wave Height from Acoustic Tide Gauges.
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- Journal of Atmospheric & Oceanic Technology, 2022, v. 39, n. 6, p. 721, doi. 10.1175/JTECH-D-20-0212.1
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- Article
The History and Practice of AI in the Environmental Sciences.
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- Bulletin of the American Meteorological Society, 2022, v. 103, n. 5, p. E1351, doi. 10.1175/BAMS-D-20-0234.1
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- Article
Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences.
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- Bulletin of the American Meteorological Society, 2021, v. 102, n. 5, p. E1016, doi. 10.1175/BAMS-D-20-0031.1
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- Article
Pricing Options on Water in Texas.
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- Texas Water Journal, 2021, v. 12, n. 1, p. 91, doi. 10.21423/twj.v12i1.7121
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- Article
Review and Evaluation of Deep Learning Architectures for Efficient Land Cover Mapping with UAS Hyper-Spatial Imagery: A Case Study Over a Wetland.
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- Remote Sensing, 2020, v. 12, n. 6, p. 959, doi. 10.3390/rs12060959
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- Article
Deep‐learning model used to predict thunderstorms within 400 km<sup>2</sup> of south Texas domains.
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- Meteorological Applications, 2020, v. 27, n. 2, p. 1, doi. 10.1002/met.1905
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- Article
A Bayesian‐Like Approach to Describe the Regional Variation of High‐Flash Rate Thunderstorms From Thermodynamic and Kinematic Environment Variables.
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- Journal of Geophysical Research. Atmospheres, 2019, v. 124, n. 23, p. 12507, doi. 10.1029/2019JD031254
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- Article
Unsupervised Clustering of Multi-Perspective 3D Point Cloud Data in Marshes: A Case Study.
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- Remote Sensing, 2019, v. 11, n. 22, p. 2715, doi. 10.3390/rs11222715
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- Article
Ensemble Neural Networks for Modeling DEM Error.
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- ISPRS International Journal of Geo-Information, 2019, v. 8, n. 10, p. 444, doi. 10.3390/ijgi8100444
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- Article
Forecasting GRACE Data over the African Watersheds Using Artificial Neural Networks.
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- Remote Sensing, 2019, v. 11, n. 15, p. 1769, doi. 10.3390/rs11151769
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- Article
Unsupervised Clustering Method for Complexity Reduction of Terrestrial Lidar Data in Marshes.
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- Remote Sensing, 2018, v. 10, n. 1, p. 133, doi. 10.3390/rs10010133
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- Article
Hypothermic stunning of green sea turtles in a western Gulf of Mexico foraging habitat.
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- PLoS ONE, 2017, v. 12, n. 3, p. 1, doi. 10.1371/journal.pone.0173920
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- Article
An artificial neural network model to predict thunderstorms within 400km<sup>2</sup> South Texas domains.
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- Meteorological Applications, 2015, v. 22, n. 3, p. 650, doi. 10.1002/met.1499
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- Article
Methodology for Applying GIS to Evaluate Hydrodynamic Model Performance in Predicting Coastal Inundation.
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- Journal of Coastal Research, 2014, v. 30, n. 5, p. 1055, doi. 10.2112/JCOASTRES-D-13-00160.1
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- Article
Spatiotemporal Predictive Models for Juvenile Southern Flounder in Texas Estuaries.
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- North American Journal of Fisheries Management, 2013, v. 33, n. 4, p. 817, doi. 10.1080/02755947.2013.811129
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A Cooperative Approach to Resource Management: Texas Game Fish Win.
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- Marine Technology Society Journal, 2010, v. 44, n. 5, p. 5, doi. 10.4031/MTSJ.44.5.5
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- Article