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Webinar: Deep Unsupervised Learning for Climate Informatics

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Tuesday, 02 March 2021, 5:00

Tuesday, March 2, 2021. 5:00 PM Eastern. Webinar: Deep Unsupervised Learning for Climate Informatics. Claire Monteleoni, University of Colorado, Boulder. Sponsored by NCAR/UCAR. More information here.

Despite the scientific consensus on climate change, drastic uncertainties remain. Crucial questions about regional climate trends, changes in extreme events, such as heat waves and mega-storms, and understanding how climate varied in the distant past, must be answered in order to improve predictions, assess impacts and vulnerability, and inform mitigation and sustainable adaptation strategies. Machine learning can help answer such questions and shed light on climate change. This talk will focus on our recent climate informatics research, in particular semi- and unsupervised deep learning approaches to studying rare and extreme events, and downscaling temperature and precipitation.

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