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Titlebook: Recent Advances in Algorithmic Differentiation; Shaun Forth,Paul Hovland,Andrea Walther Conference proceedings 2012 Springer-Verlag Berlin

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On the Efficient Computation of Sparsity Patterns for Hessians,two algorithms to detect the sparsity pattern of Hessians: An approach for the computation of exact sparsity patterns and a second one for the overestimation of sparsity patterns. For both algorithms, corresponding complexity results are stated. Subsequently, new data structures and set operations a
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Automatic Differentiation Through the Use of Hyper-Dual Numbers for Second Derivatives,ent mathematical properties of generalized complex numbers that enable first-derivative information to be carried in the non-real part of the number. These methods are capable of producing effectively exact derivative values. However, when second-derivative information is desired, generalized comple
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Hierarchical Algorithmic Differentiation A Case Study, atmospheric remote sensing problem. In-depth structural and performance analyses allow for the run time factor between the adjoint generated by overloading in C++ and the original forward simulation to be reduced to 3. 5. The dense Jacobian matrix of the underlying problem is computed at the same c
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Storing Versus Recomputation on Multiple DAGs,g the adjoint sweep, in practice, only the store-all or recompute-all approaches are fully automated. This paper considers a heuristic approach for exploiting finer granularity recomputations to reduce the storage requirements and thereby improve the overall adjoint efficiency without the need for m
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