Development and Interpretation of a Neural Network-Based Synthetic Radar Reflectivity Estimator Using GOES-R Satellite Observations

16 April 2020

Papers citing "Development and Interpretation of a Neural Network-Based Synthetic Radar Reflectivity Estimator Using GOES-R Satellite Observations"

7 / 7 papers shown

Title
SRViT: Vision Transformers for Estimating Radar Reflectivity from Satellite Observations at Scale Jason Stock Kyle Hilburn Imme Ebert-Uphoff Charles Anderson 40 1 0 20 Jun 2024
Developing a Series of AI Challenges for the United States Department of the Air Force V. Gadepally Greg Angelides Andrei Barbu Andrew Bowne L. Brattain ... Mark S. Veillette Matthew L. Weiss Allan B. Wollaber S. Yuditskaya J. Kepner AI4CE 23 5 0 14 Jul 2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience Antonios Mamalakis E. Barnes I. Ebert‐Uphoff 31 73 0 07 Feb 2022
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences A. McGovern I. Ebert‐Uphoff D. Gagne A. Bostrom 21 64 0 15 Dec 2021
CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences -- Version 1 I. Ebert‐Uphoff Ryan Lagerquist Kyle Hilburn Yoonjin Lee Katherine Haynes Jason Stock C. Kumler J. Stewart 24 20 0 17 Jun 2021
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications I. Ebert‐Uphoff Kyle Hilburn 26 30 0 06 May 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017