Physical Interpretability of Empirical Models


Description:

This session seeks presentations that describe ways to interpret empirical and machine learning models, including interpretable and post hoc explanations


Papers:
Meteorological Interpretation of XAI Output Applied to a 3D Convolutional Neural Network Fog Prediction Model
Waylon G. Collins, NOAA/National Weather Service, Corpus Christi, TX; and E. Krell, P. E. Tissot, and S. A. King

Submission Deadline: Thursday, 31 August 2023