@misc {23582,
	title = {Dolfin-adjoint: Automatic adjoint models for FEniCS},
	howpublished = {The 8th International Congress on Industrial and Applied Mathematics},
	year = {2015},
	publisher = {The 8th International Congress on Industrial and Applied Mathematics},
	address = {Beijing, China},
	abstract = {Adjoint and tangent linear models form the basis of many numerical techniques, including sensitivityanalysis, optimization and stability analysis. The implementation of adjoint models for nonlinear or time-dependent models are notoriously challenging: the manual approach is time-consuming and traditionalautomatic differentiation tools lack robustness and performance.dolfin-adjoint solves this problem by automatically analyzing the high-level mathematical structureinherent in finite element methods. It raises the traditional abstraction of algorithmic differentiationfrom the level of individual floating point operations to that of whole systems of differential equations.This approach delivers a number of advantages over the previous state-of-the-art: robust hands-offautomation of adjoint model derivation, optimal computational efficiency, and native parallel support.},
	author = {Simon W {Funke} and Patrick Emmet {Farrell} and David A. {Ham} and Marie E. {Rognes}}
}
