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
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability B. Toms E. Barnes I. Ebert‐Uphoff AI4CE 73 215 0 04 Dec 2019
Distributed Deep Learning for Precipitation Nowcasting S. Samsi Christopher J. Mattioli Mark S. Veillette 67 23 0 28 Aug 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 104 1,021 0 26 Feb 2019
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 293 2,271 0 24 Jun 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 207 2,236 0 12 Jun 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks Wenjie Luo Yujia Li R. Urtasun R. Zemel HAI 102 1,803 0 15 Jan 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.9K 77,441 0 18 May 2015