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Using spatiotemporal relational random forests to improve our understanding of severe weather processes., , , , , and . Statistical Analysis and Data Mining, 4 (4): 407-429 (2011)Spatiotemporal Relational Probability Trees: An Introduction., , , , and . ICDM, page 935-940. IEEE Computer Society, (2008)Welcome to AI matters 5(2)., and . AI Matters, 5 (2): 3 (2019)AI profiles: an interview with Maja Matarić., and . AI Matters, 3 (3): 12-14 (2017)Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning., , , , and . Machine Learning, 95 (1): 27-50 (2014)Creating significant learning experiences in introductory artificial intelligence., and . SIGCSE, page 39-43. ACM, (2007)A Summary of the Twenty-Ninth AAAI Conference on Artificial Intelligence., , , , , , , , , and 9 other author(s). AI Magazine, 36 (3): 99-106 (2015)ACM SIGAI activity report., , , , , , , , , and 7 other author(s). AI Matters, 5 (3): 6-11 (2019)Day-Ahead Hail Prediction Integrating Machine Learning with Storm-Scale Numerical Weather Models., , , , , and . AAAI, page 3954-3960. AAAI Press, (2015)Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines., and . ICDM Workshops, page 359-368. IEEE Computer Society, (2008)