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10/22/2022
Tools for Extracting Spatio-Temporal Patterns in Meteorological Image Sequences: From Feature Engineering to Attention-Based Neural Networks
Atmospheric processes involve both space and time. This is why human ana...
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08/19/2022
Carefully choose the baseline: Lessons learned from applying XAI attribution methods for regression tasks in geoscience
Methods of eXplainable Artificial Intelligence (XAI) are used in geoscie...
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07/21/2022
A Primer on Topological Data Analysis to Support Image Analysis Tasks in Environmental Science
Topological data analysis (TDA) is a tool from data science and mathemat...
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03/21/2022
Can we integrate spatial verification methods into neural-network loss functions for atmospheric science?
In the last decade, much work in atmospheric science has focused on spat...
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02/07/2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience
Convolutional neural networks (CNNs) have recently attracted great atten...
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12/15/2021
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences
Given the growing use of Artificial Intelligence (AI) and machine learni...
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06/17/2021
CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences – Version 1
Neural networks are increasingly used in environmental science applicati...
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03/18/2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset
Despite the increasingly successful application of neural networks to ma...
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05/06/2020
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications
Neural networks have opened up many new opportunities to utilize remotel...
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04/16/2020
Development and Interpretation of a Neural Network-Based Synthetic Radar Reflectivity Estimator Using GOES-R Satellite Observations
The objective of this research is to develop techniques for assimilating...
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12/04/2019
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability
Neural networks have become increasingly prevalent within the geoscience...
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01/23/2019
New Exploratory Tools for Extremal Dependence: Chi Networks and Annual Extremal Networks
Understanding dependence structure among extreme values plays an importa...
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11/13/2017
Machine Learning for the Geosciences: Challenges and Opportunities
Geosciences is a field of great societal relevance that requires solutio...
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09/12/2017