Mathematics and Machine Learning for Earth System Simulation 2/2-6/26

Modern scientific progress is often driven by numerical computations and simulations to represent large numbers of complex and interrelated physical processes. In recent years, machine learning (ML) applications in earth system simulation and prediction have promised to accelerate the accuracy and computational processing power of Earth system models including physics-constrained approaches, super ultra-high resolution, large language models for earth systems, and uncertainty quantification.
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