ADiMat is a software tool implementing the technology of automatic differentiation (AD) to programs written in MATLAB which is a trademark of The Mathworks, Inc. ADiMat is based on a source transformation approach. That is, it transforms a given MATLAB code for the evaluation of some mathematical function into a new MATLAB code for the evaluation of user-specified derivatives of that function.

References in zbMATH (referenced in 18 articles , 2 standard articles )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Baydin, Atılım Güneş; Pearlmutter, Barak A.; Radul, Alexey Andreyevich; Siskind, Jeffrey Mark: Automatic differentiation in machine learning: a survey (2018)
  2. Bücker, H. Martin; Willkomm, Johannes: Estimating the expansion coefficients of a geomagnetic field model using first-order derivatives of associated Legendre functions (2018)
  3. Duarte, Belmiro P. M.; Sagnol, Guillaume; Wong, Weng Kee: An algorithm based on semidefinite programming for finding minimax optimal designs (2018)
  4. Duarte, Belmiro P. M.; Wong, Weng Kee; Dette, Holger: Adaptive grid semidefinite programming for finding optimal designs (2018)
  5. Jiang, Ting; Zhou, XiaoJian: Gradient/Hessian-enhanced least square support vector regression (2018)
  6. Di, Zichao (Wendy); Leyffer, Sven; Wild, Stefan M.: Optimization-based approach for joint X-ray fluorescence and transmission tomographic inversion (2016)
  7. Meyer, C.; Schnepp, S. M.; Thoma, O.: Optimal control of the inhomogeneous relativistic Maxwell-Newton-Lorentz equations (2016)
  8. Sluşanschi, Emil I.; Dumitrel, Vlad: ADiJaC -- automatic differentiation of Java classfiles (2016)
  9. Khuvis, Samuel; Gobbert, Matthias K.; Peercy, Bradford E.: Time-stepping techniques to enable the simulation of bursting behavior in a physiologically realistic computational islet (2015)
  10. Moré, Jorge J.; Wild, Stefan M.: Do you trust derivatives or differences? (2014)
  11. Charpentier, I.: On higher-order differentiation in nonlinear mechanics (2012)
  12. Rund, Armin; Chudej, Kurt; Kerler, Johanna; Pesch, Hans Josef; Sternberg, Kati: Optimal control of coupled multiphysics problems: Guidelines for real-life applications demonstrated for a complex fuel cell model (2012)
  13. Lampoh, Komlanvi; Charpentier, Isabelle; Daya, El Mostafa: A generic approach for the solution of nonlinear residual equations. III: Sensitivity computations (2011)
  14. Bischof, Christian H.; Hovland, Paul D.; Norris, Boyana: On the implementation of automatic differentiation tools (2008)
  15. Bücker, H. Martin; Petera, Monika; Vehreschild, Andre: Code optimization techniques in source transformations for interpreted languages (2008)
  16. Bücker, H. Martin; Vehreschild, Andre: Coping with a variable number of arguments when transforming MATLAB programs (2008)
  17. Bischof, Christian H.; Bücker, H. Martin; Vehreschild, Andre: A macro language for derivative definition in ADiMat (2006)
  18. Bischof, Christian; Lang, Bruno; Vehreschild, Andre: Automatic differentiation for MATLAB programs (2003)

Further publications can be found at: