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2020 – today
- 2024
[i8]Jason Stock, Kyle Hilburn, Imme Ebert-Uphoff, Charles W. Anderson:
SRViT: Vision Transformers for Estimating Radar Reflectivity from Satellite Observations at Scale. CoRR abs/2406.16955 (2024)- 2023
- [j4]Yifan Yang
, Haonan Chen, Kyle A. Hilburn, Robert J. Kuligowski, Robert Cifelli:
Deep Learning for Precipitation Retrievals Using ABI and GLM Measurements on the GOES-R Series. IEEE Trans. Geosci. Remote. Sens. 61: 1-14 (2023) - [c6]Yifan Yang, Alexander C. Hu, Haonan Chen, Kyle A. Hilburn:
Precipitation Retrieval Using ABI and GLM Measurements on the Goes-R Series. IGARSS 2023: 1822-1825 - [i7]Jan Mandel, J. Hirschi, Adam K. Kochanski, Angel Farguell, J. Haley, Derek V. Mallia, Bryan Shaddy, Assad A. Oberai, Kyle A. Hilburn:
Building a Fuel Moisture Model for the Coupled Fire-Atmosphere Model WRF-SFIRE from Data: From Kalman Filters to Recurrent Neural Networks. CoRR abs/2301.05427 (2023) - [i6]Bryan Shaddy, Deep Ray, Angel Farguell, Valentina Calaza, Jan Mandel, James Haley, Kyle Hilburn, Derek V. Mallia, Adam K. Kochanski, Assad A. Oberai:
Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts. CoRR abs/2309.02615 (2023) - 2022
- [i5]Akansha Singh Bansal, Yoonjin Lee, Kyle Hilburn, Imme Ebert-Uphoff:
Tools for Extracting Spatio-Temporal Patterns in Meteorological Image Sequences: From Feature Engineering to Attention-Based Neural Networks. CoRR abs/2210.12310 (2022) - 2021
- [j3]Angel Farguell, Jan Mandel, James Haley, Derek V. Mallia, Adam K. Kochanski, Kyle Hilburn:
Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data. Remote. Sens. 13(11): 2203 (2021) - [i4]Jan Mandel, Angel Farguell, Adam K. Kochanski, Derek V. Mallia, Kyle Hilburn:
Simple finite elements and multigrid for efficient mass-consistent wind downscaling in a coupled fire-atmosphere model. CoRR abs/2101.08453 (2021) - [i3]Imme Ebert-Uphoff, Ryan Lagerquist, Kyle Hilburn, Yoonjin Lee, Katherine Haynes, Jason Stock, Christina Kumler, Jebb Q. Stewart:
CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences - Version 1. CoRR abs/2106.09757 (2021) - 2020
- [i2]Kyle A. Hilburn, Imme Ebert-Uphoff, Steven D. Miller:
Development and Interpretation of a Neural Network-Based Synthetic Radar Reflectivity Estimator Using GOES-R Satellite Observations. CoRR abs/2004.07906 (2020) - [i1]Imme Ebert-Uphoff, Kyle A. Hilburn:
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications. CoRR abs/2005.03126 (2020)
2010 – 2019
- 2019
- [c5]Jan Mandel, Martin Vejmelka, Adam K. Kochanski, Angel Farguell, James Haley, Derek V. Mallia, Kyle Hilburn:
An Interactive Data-Driven HPC System for Forecasting Weather, Wildland Fire, and Smoke. UrgentHPC@SC 2019: 35-44 - 2018
- [j2]Ruanyu Zhang, Zhenzhan Wang, Kyle A. Hilburn:
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm. Remote. Sens. 10(11): 1770 (2018) - 2016
- [j1]Kyle A. Hilburn, Thomas Meissner, Frank J. Wentz, Shannon T. Brown:
Ocean Vector Winds From WindSat Two-Look Polarimetric Radiances. IEEE Trans. Geosci. Remote. Sens. 54(2): 918-931 (2016) - 2014
- [c4]Thomas Meissner, Frank Wentz, Joel Scott, Kyle Hilburn:
Upper ocean salinity stratification and rain freshening in the tropics observed from Aquarius. IGARSS 2014: 5111-5114 - 2012
- [c3]Thomas Meissner, Frank Wentz, Kyle Hilburn, Gary S. E. Lagerloef, David M. Le Vine:
The Aquarius salinity retrieval algorithm. IGARSS 2012: 386-388 - 2011
- [c2]Chung-Lin Shie, Kyle Hilburn:
A newly revived Satellite-based Global air-sea Surface Turbulent Fluxes dataset and its dependence on the SSM/I brightness temperature. IGARSS 2011: 2085-2088
2000 – 2009
- 2003
- [c1]Kyle Hilburn, Frank Wentz, Carl A. Mears:
Rain effects on SeaWinds data. IGARSS 2003: 2971-2976
Coauthor Index
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