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Title: A tutorial on automatic differentiation for scientific design: practical, elegant and powerful

Speaker: Nick McGreivy

Video: The Talk's video available on YouTube.

When: 09 Mar 2021, 18:00 (CET)

Hosted by: Oak Nelson

Abstract: Automatic differentiation (AD) is a numerical technique for computing the derivative of a function specified as a computer program. Although AD was invented decades ago, it wasn’t until the recent interest in machine learning and the associated development of high-quality automatic differentiation frameworks that the benefits of AD in physics were more widely recognized. In this tutorial, I introduce AD. By the end of the tutorial, you will hopefully understand the fundamentals of how AD works in theory and how it is used in practice. For a short, 5-minute introduction to AD, feel free to read this and this

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