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Thrilled and honored to present Deep Analytics in Tokyo next month.
The second part of my paper “Computation graphs for AAD and Machine Learning part II: Adjoint differentiation and AAD” was just published in Wilmott, the second in a series of three articles with code dedicated to AAD and Computational Finance in general. It covers computation graphs, backpropagation, AAD and implementation in finance, taking inspiration in the recent achievements of the Superfly Analytics group of Danske Bank.
The first part was published in Wilmott November 2019 issue.
TensorFlow makes it particularly easy to implement simple Monte-Carlo simulations on GPU. To be followed.