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ML for High-Performance Climate: Data Post Processing, Compression, and Earth Virtualization Engines

Offered By: Scalable Parallel Computing Lab, SPCL @ ETH Zurich via YouTube

Tags

Machine Learning Courses Data Analysis Courses Scientific Computing Courses Parallel Computing Courses High Performance Computing Courses Climate Science Courses Climate Modeling Courses

Course Description

Overview

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Explore cutting-edge applications of machine learning in high-performance climate science, focusing on data post-processing, compression techniques, and Earth virtualization engines. Delve into advanced topics presented by experts from the Scalable Parallel Computing Lab at ETH Zurich in this comprehensive 68-minute conference talk. Gain insights into how ML is revolutionizing climate data handling, enhancing computational efficiency, and enabling more accurate Earth system simulations. Learn about innovative approaches to tackle the challenges of processing and storing massive climate datasets, and discover how Earth virtualization engines are transforming our ability to model and understand complex climate systems.

Syllabus

ML for High-Performance Climate: Data Post Processing, Compression, and Earth Virtualization Engines


Taught by

Scalable Parallel Computing Lab, SPCL @ ETH Zurich

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