引用次数
引用: 5,719
H-指数: 38
I10-指数 : 80
出版物: 243
Causal discovery in the presence of confounding latent variables for climate science
Savini Samarasinghe , Elizabeth A Barnes , Imme Ebert-Uphoff
International Workshop on Climate Informatics: CI 53 -56
4
2018
AStudy OF CAUSAL LINKS BETWEEN THE ARCTIC AND THE MIDLATITUDE JET-STREAMS
Savini Samarasinghe , Marie McGraw , Elizabeth A Barnes , Imme Ebert-Uphoff
Proceedings of the 7th International Workshop on Climate Informatics
2
2017
Leveraging Interpretable Neural Networks for Scientific Discovery
Elizabeth A Barnes , Kirsten J Mayer , Jamin Rader , Benjamin A Toms
AGU Fall Meeting Abstracts 2020 A069 -03
1
2020
Strengthened causal connections between the MJO and the North Atlantic with climate warming
Savini M Samarasinghe , Elizabeth A Barnes , Charlotte Connolly , Imme Ebert-Uphoff
Authorea Preprints
2022
Explainable Artificial Intelligence for Environmental Science: Introducing Objectivity into the Assessment of Neural Network Attribution Methods
Antonios Mamalakis , Imme Ebert-Uphoff , Elizabeth Barnes
102nd American Meteorological Society Annual Meeting
2022
Strengthening Causal Connections Between the MJO and the North Atlantic in Future Climate Projections
Savini Manthila Samarasinghe , Elizabeth A Barnes , Charlotte Connolly , Imme Ebert-Uphoff
AGU Fall Meeting Abstracts 2020 A246 -06
2020
Selected Methods from Explainable AI to Improve Understanding of Neural Network Reasoning for Environmental Science Applications
Imme Ebert-Uphoff , K Hilburn , Benjamin A Toms , Elizabeth A Barnes
100th American Meteorological Society Annual Meeting
2020
NSF AI institute for research on trustworthy AI in weather, climate, and coastal oceanography (AI2ES)
Amy McGovern , Ann Bostrom , Phillip Davis , Julie L Demuth
Bulletin of the American Meteorological Society 103 ( 7) E1658 -E1668
8
2022
Using Grouped Features to Improve Explainable AI Results for Atmospheric AI Models that use Gridded Spatial Data and Complex Machine Learning Technique
Evan Krell , Philippe Tissot , Antonios Mamalakis , Waylon Collins
Authorea Preprints
2024
Exploring the Influence of Correlated Features on Geoscience AI Models to Improve the Scientific Insights Gained From Using Explainable AI Techniques for Feature Attribution
Evan Krell , Antonios Mamalakis , Imme Ebert-Uphoff , Philippe Tissot
AGU23
2023
Trustworthy AI for Extreme Event Prediction and Understanding
Amy McGovern , Ann Bostrom , Phillip Davis , Julie Demuth
Office of Scientific and Technical Information (OSTI)
2021
Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science
Amy McGovern , Imme Ebert-Uphoff , David John Gagne , Ann Bostrom
Environmental Data Science 1 e6 -e6
57
2022
Exploring what AI/ML guidance features NWS forecasters deem trustworthy
Mariana Goodall Cains , Christopher D Wirz , Julie L Demuth , Ann Bostrom
103rd AMS Annual Meeting
3
2023
Classifying and Addressing Bias in AI/ML for the Earth Sciences
Amy McGovern , Ann Bostrom , David John Gagne , Imme Ebert-Uphoff
103rd AMS Annual Meeting
2
2023
NWS forecasters’ perceptions and potential uses of trustworthy AI/ML for hazardous weather risks
Mariana Goodall Cains , Christopher D Wirz , Julie L Demuth , Ann Bostrom
102nd American Meteorological Society Annual Meeting
1
2022
Visualizing Data-Driven AI Models to Engage Operational Forecasters
Jacob T Radford , Imme Ebert-Uphoff , Jebb Q Stewart , Robert T DeMaria
104th AMS Annual Meeting
2024
Identifying and Categorizing Bias in AI/ML for Earth Sciences
Amy McGovern , Ann Bostrom , Marie McGraw , Randy J Chase
Bulletin of the American Meteorological Society
2024
Creating Personalized Learning Journeys for All Levels of Learning in AI with Applications to Weather and Climate
Amy McGovern , David John Gagne , Imme Ebert-Uphoff , Ann Bostrom
103rd AMS Annual Meeting
2023
Ethical and Responsible AI and Trust for Weather and Climate
Amy McGovern , Imme Ebert-Uphoff , Ann Bostrom , David John Gagne
102nd American Meteorological Society Annual Meeting
2022
AI2ES: Alpha-Institute—Artificial Intelligence for Environmental Sciences
Amy McGovern , Jason Hickey , David Hall , Imme Ebert-Uphoff
100th American Meteorological Society Annual Meeting
2020