Differentiable Programming for Oceanography with Patrick Heimbach - #557
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Differentiable Programming in Oceanography
This chapter explores the significance of differentiable programming in enhancing oceanographic modeling, focusing on the integration of observational data and physical models. It highlights advancements in global ocean data assimilation using automatic differentiation, particularly with the Julia programming language, and discusses collaborative efforts to improve climate modeling through machine learning techniques.
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