Andrea Walther
Andrea Walther
Professor of Mathematics, Humboldt-Universität zu Berlin
Verified email at - Homepage
Cited by
Cited by
Evaluating derivatives: principles and techniques of algorithmic differentiation
A Griewank, A Walther
Society for industrial and applied mathematics, 2008
Algorithm 799: revolve: an implementation of checkpointing for the reverse or adjoint mode of computational differentiation
A Griewank, A Walther
ACM Transactions on Mathematical Software (TOMS) 26 (1), 19-45, 2000
Getting Started with ADOL-C.
A Walther, A Griewank
Combinatorial scientific computing 181, 202, 2009
Evaluating higher derivative tensors by forward propagation of univariate Taylor series
A Griewank, J Utke, A Walther
Mathematics of computation 69 (231), 1117-1130, 2000
On constrained optimization by adjoint based quasi-Newton methods
A Griewank, A Walther
Optimization Methods and Software 17 (5), 869-889, 2002
Automatic differentiation of explicit Runge-Kutta methods for optimal control
A Walther
Computational Optimization and Applications 36 (1), 83-108, 2007
Efficient computation of sparse Hessians using coloring and automatic differentiation
AH Gebremedhin, A Tarafdar, A Pothen, A Walther
INFORMS Journal on Computing 21 (2), 209-223, 2009
An adjoint-based SQP algorithm with quasi-Newton Jacobian updates for inequality constrained optimization
M Diehl, A Walther, HG Bock, E Kostina
Optimization Methods & Software 25 (4), 531-552, 2010
Program reversal schedules for single and multi-processor machines
A Walther
Dresden, Techn. Univ., Diss., 1999, 1999
Multistage approaches for optimal offline checkpointing
P Stumm, A Walther
SIAM Journal on Scientific Computing 31 (3), 1946-1967, 2009
Advantages of binomial checkpointing for memory-reduced adjoint calculations
A Walther, A Griewank
Numerical mathematics and advanced applications, 834-843, 2004
Computing sparse Hessians with automatic differentiation
A Walther
ACM Transactions on Mathematical Software (TOMS) 34 (1), 1-15, 2008
Evaluating gradients in optimal control: continuous adjoints versus automatic differentiation
R Griesse, A Walther
Journal of optimization theory and applications 122 (1), 63-86, 2004
ADOL‐C: automatic differentiation using operator overloading in C++
A Walther, A Griewank, O Vogel
PAMM: Proceedings in Applied Mathematics and Mechanics 2 (1), 41-44, 2003
Automatic differentiation of an entire design chain for aerodynamic shape optimization
NR Gauger, A Walther, C Moldenhauer, M Widhalm
New Results in Numerical and Experimental Fluid Mechanics VI, 454-461, 2007
First-and second-order optimality conditions for piecewise smooth objective functions
A Griewank, A Walther
Optimization Methods and Software 31 (5), 904-930, 2016
On the efficient computation of high-order derivatives for implicitly defined functions
M Wagner, A Walther, BJ Schaefer
Computer Physics Communications 181 (4), 756-764, 2010
New algorithms for optimal online checkpointing
P Stumm, A Walther
SIAM Journal on Scientific Computing 32 (2), 836-854, 2010
An optimal memory‐reduced procedure for calculating adjoints of the instationary Navier‐Stokes equations
M Hinze, A Walther, J Sternberg
Optimal Control Applications and Methods 27 (1), 19-40, 2006
Algorithmic differentiation of the Open CASCADE Technology CAD kernel and its coupling with an adjoint CFD solver
M Banović, O Mykhaskiv, S Auriemma, A Walther, H Legrand, JD Müller
Optimization Methods and Software 33 (4-6), 813-828, 2018
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