Adjoint Algorithmic Differentiation Masterclass - New York 2019
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Description
This two-day course, provides a practical introduction to algorithmic differentiation (AD). Attendees will discuss the mathematical foundations for adjoints methods, algorithmic differentiation (AD) as a general computational technique for the efficient calculation of price sensitivities, and the use of AD software as a way to generate the adjoint code. Focus will be placed on its application to Monte Carlo methods for SDEs and finite difference methods for PDEs.
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