Amy McGovern
Orcid: 0000-0001-6675-7119
According to our database1,
Amy McGovern
authored at least 65 papers
between 1998 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
AI2ES: The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography.
AI Mag., 2024
2023
2022
Comparing Explanation Methods for Traditional Machine Learning Models Part 2: Quantifying Model Explainability Faithfulness and Improvements with Dimensionality Reduction.
CoRR, 2022
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement.
CoRR, 2022
A Machine Learning Tutorial for Operational Meteorology, Part II: Neural Networks and Deep Learning.
CoRR, 2022
A Machine Learning Tutorial for Operational Meteorology, Part I: Traditional Machine Learning.
CoRR, 2022
2021
CREST-iMAP v1.0: A fully coupled hydrologic-hydraulic modeling framework dedicated to flood inundation mapping and prediction.
Environ. Model. Softw., 2021
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences.
CoRR, 2021
2020
Using Machine Learning to Calibrate Storm-Scale Probabilistic Guidance of Severe Weather Hazards in the Warn-on-Forecast System.
CoRR, 2020
NSF AI institute for research on trustworthy ai in weather, climate, and coastal oceanography.
AI Matters, 2020
2019
2018
2017
Proceedings of the Practice and Experience in Advanced Research Computing 2017: Sustainability, 2017
Proceedings of the 2017 IEEE Frontiers in Education Conference, 2017
2016
Proceedings of the 16th Eurographics Symposium on Parallel Graphics and Visualization, 2016
2015
AI Mag., 2015
Day-Ahead Hail Prediction Integrating Machine Learning with Storm-Scale Numerical Weather Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning.
Mach. Learn., 2014
2013
Data Min. Knowl. Discov., 2013
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013
Proceedings of the IEEE Frontiers in Education Conference, 2013
2012
Using the XSEDE supercomputing and visualization resources to improve tornado prediction using data mining.
Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment, 2012
Learning ensembles of Continuous Bayesian Networks: An application to rainfall prediction.
Proceedings of the 2012 Conference on Intelligent Data Understanding, 2012
Proceedings of the 2012 Conference on Intelligent Data Understanding, 2012
2011
Using spatiotemporal relational random forests to improve our understanding of severe weather processes.
Stat. Anal. Data Min., 2011
Identifying predictive multi-dimensional time series motifs: an application to severe weather prediction.
Data Min. Knowl. Discov., 2011
Proceedings of the 2nd International EuroVis Workshop on Visual Analytics, 2011
Proceedings of the Second Symposium on Education Advances in Artificial Intelligence, 2011
2010
Proceedings of the 2010 Conference on Intelligent Data Understanding, 2010
2009
Proceedings of the ICDM Workshops 2009, 2009
Proceedings of the ICDM Workshops 2009, 2009
2008
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008
Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines.
Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008
2007
Proceedings of the 38th SIGCSE Technical Symposium on Computer Science Education, 2007
Proceedings of the IJCAI 2007, 2007
2003
Exploiting relational structure to understand publication patterns in high-energy physics.
SIGKDD Explor., 2003
Identifying Predictive Structures in Relational Data Using Multiple Instance Learning.
Proceedings of the Machine Learning, 2003
2002
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts.
Mach. Learn., 2002
Proceedings of the Abstraction, 2002
2001
Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001
1998
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998
Proceedings of the Second International Conference on Autonomous Agents, 1998