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VERSION:2.0
PRODID:-//DP Pro Event Calendar//3.2.6//EN
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UID:e9d4bf66-8121-44f0-9e06-5d8e233276e2
DTSTART;TZID=Europe/Paris:20210710T163000
DTEND;TZID=Europe/Paris:20210710T173000
DTSTAMP:20210601T143125Z
SUMMARY:Climate Informatics: Machine Learning for the Study of Climate Change
DESCRIPTION: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. I will give an overview of our climate informatics research\, focusing on challenges in learning from spatiotemporal data\, along with semi- and unsupervised deep learning approaches to studying rare and extreme events\, and precipitation and temperature downscaling.
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