Titlebook: Automatic Differentiation: Applications, Theory, and Implementations; Martin Bücker,George Corliss,Boyana Norris Conference proceedings 20

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978-3-540-28403-1Springer-Verlag Berlin Heidelberg 2006

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Semiautomatic Differentiation for Efficient Gradient Computations, can deliver gradients efficiently and accurately. This paper concerns on-going work; it compares several implementations of backward AD, describes a simple operator-overloading implementation specialized for gradient computations, and compares the implementations on some mesh-optimization examples.

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Transforming Equation-Based Models in Process Engineering,endent from a specific modeling language. Hence, CapeML is the adequate format to which automatic differentiation is applied in this dynamic optimization framework. A novel system called ADiCape is proposed, implementing the forward mode for models written in the XML-based language CapeML. This AD t

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Coping With Addictive Opioid Markets brief survey, a view of present tasks and future prospects focuses on the need for further education, communication of results, and expansion of areas of application of AD. In addition, some final remarks are made concerning extension of the method of algorithm transformation to problems other than

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Joy Kemp,Gaynor D. Maclean,Nester Moyo can deliver gradients efficiently and accurately. This paper concerns on-going work; it compares several implementations of backward AD, describes a simple operator-overloading implementation specialized for gradient computations, and compares the implementations on some mesh-optimization examples.

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https://doi.org/10.1057/9781137007124endent from a specific modeling language. Hence, CapeML is the adequate format to which automatic differentiation is applied in this dynamic optimization framework. A novel system called ADiCape is proposed, implementing the forward mode for models written in the XML-based language CapeML. This AD t