Advances in Automatic Differentiation – Bischof, C.H
This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in …
This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.
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2018年4月30日 - Automatic differentiation (AD), also called algorithmic differentiation or simply “auto- ... pentier and Ghemires, 2000), and computational finance (Bischof et al., ... In C. H. Bischof, H. M. Bücker, P. Hovland, U. Naumann, and. J. Utke, editors, Advances in Automatic Differentiation, volume 64 of Lecture Notes in.
Keywords: automatic differentiation, ADIC2, sparse derivative computation, ColPack ...  V. Pascual, L. Hascoët, TAPENADE for C, in: C. H. Bischof, H. M. Bücker, ... U. Naumann, J. Utke (Eds.), Advances in Automatic Differentiation, Springer,...