Amy McGovern
Zitiert von
Zitiert von
Automatic discovery of subgoals in reinforcement learning using diverse density
A McGovern, AG Barto
Using artificial intelligence to improve real-time decision-making for high-impact weather
A McGovern, KL Elmore, DJ Gagne, SE Haupt, CD Karstens, R Lagerquist, ...
Bulletin of the American Meteorological Society 98 (10), 2073-2090, 2017
Making the black box more transparent: Understanding the physical implications of machine learning
A McGovern, R Lagerquist, DJ Gagne, GE Jergensen, KL Elmore, ...
Bulletin of the American Meteorological Society 100 (11), 2175-2199, 2019
Identifying predictive multi-dimensional time series motifs: an application to severe weather prediction
A McGovern, DH Rosendahl, RA Brown, KK Droegemeier
Data Mining and Knowledge Discovery 22, 232-258, 2011
Storm-based probabilistic hail forecasting with machine learning applied to convection-allowing ensembles
DJ Gagne, A McGovern, SE Haupt, RA Sobash, JK Williams, M Xue
Weather and forecasting 32 (5), 1819-1840, 2017
Roles of macro-actions in accelerating reinforcement learning
A McGovern, RS Sutton, AH Fagg
Grace Hopper celebration of women in computing 1317, 15, 1997
Autonomous discovery of temporal abstractions from interaction with an environment
EA Mcgovern
University of Massachusetts Amherst, 2002
Macro-actions in reinforcement learning: An empirical analysis
A McGovern, RS Sutton
Computer Science Department Faculty Publication Series, 15, 1998
Deep learning for spatially explicit prediction of synoptic-scale fronts
R Lagerquist, A McGovern, DJ Gagne II
Weather and Forecasting 34 (4), 1137-1160, 2019
Machine learning for real-time prediction of damaging straight-line convective wind
R Lagerquist, A McGovern, T Smith
Weather and Forecasting 32 (6), 2175-2193, 2017
Machine learning enhancement of storm-scale ensemble probabilistic quantitative precipitation forecasts
DJ Gagne, A McGovern, M Xue
Weather and Forecasting 29 (4), 1024-1043, 2014
Exploiting relational structure to understand publication patterns in high-energy physics
A McGovern, L Friedland, M Hay, B Gallagher, A Fast, J Neville, D Jensen
Acm Sigkdd Explorations Newsletter 5 (2), 165-172, 2003
Classification of convective areas using decision trees
DJ Gagne, A McGovern, J Brotzge
Journal of Atmospheric and Oceanic Technology 26 (7), 1341-1353, 2009
Building a basic block instruction scheduler with reinforcement learning and rollouts
A McGovern, E Moss, AG Barto
Machine learning 49, 141-160, 2002
Deep learning on three-dimensional multiscale data for next-hour tornado prediction
R Lagerquist, A McGovern, CR Homeyer, DJ Gagne II, T Smith
Monthly Weather Review 148 (7), 2837-2861, 2020
Scheduling straight-line code using reinforcement learning and rollouts
A McGovern, J Moss
Advances in neural information processing Systems 11, 1998
Evaluating knowledge to support climate action: A framework for sustained assessment. Report of an independent advisory committee on applied climate assessment
RH Moss, S Avery, K Baja, M Burkett, AM Chischilly, J Dell, PA Fleming, ...
Weather, climate, and society 11 (3), 465-487, 2019
Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning
A McGovern, DJ Gagne, JK Williams, RA Brown, JB Basara
Machine learning 95, 27-50, 2014
Spatiotemporal relational probability trees: An introduction
A McGovern, NC Hiers, M Collier, DJ Gagne II, RA Brown
2008 Eighth IEEE International Conference on Data Mining, 935-940, 2008
Teaching introductory artificial intelligence through java-based games
A McGovern, Z Tidwel, D Rushing
Proceedings of the AAAI Conference on Artificial Intelligence 25 (3), 1729-1736, 2011
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