Automatic Differentiation of C++ Codes for Large-Scale Scientific Computing
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/11758549_73
Reference10 articles.
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2. Tijskens, E., Roose, D., Ramon, H., De Baerdemaeker, J.: Automatic differentiation for nonlinear partial differential equations: An efficient operator overloading approach. Numerical Algorithms 30, 259–301 (2002)
3. Frontiers in Appl. Math.;A. Griewank,2000
4. Aubert, P., Di Césaré, N., Pironneau, O.: Automatic differentiation in C++ using expression templates and application to a flow control problem. Computing and Visualisation in Sciences 3, 197–208 (2001)
5. Lecture Notes in Computational Science and Engineering;D.M. Gay,2005
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