The Art of Differentiating Computer Programs U Naumann SIAM, 2012 | 320* | 2012 |

Automatic Differentiation of Algorithms: From Simulation to Optimization G Corliss, C Faure, A Griewank, L Hascoet, U Naumann Springer, 2001 | 318* | 2001 |

Automatic Differentiation: Applications, Theory, and Implementations, number 50 in LNCSE M Bücker, G Corliss, P Hovland, U Naumann, B Norris Springer, 2006 | 190* | 2006 |

OpenAD/F: A modular open-source tool for automatic differentiation of Fortran codes J Utke, U Naumann, M Fagan, N Tallent, M Strout, P Heimbach, C Hill, ... ACM Transactions on Mathematical Software (TOMS) 34 (4), 1-36, 2008 | 157 | 2008 |

Advances in Automatic Differentiation CH Bischof, HM Bücker, PD Hovland, U Naumann, J Utke Springer, Berlin, 2008 | 112 | 2008 |

“To be recorded” analysis in reverse-mode automatic differentiation L Hascoët, U Naumann, V Pascual Future Generation Computer Systems 21 (8), 1401-1417, 2005 | 100 | 2005 |

Combinatorial Scientific Computing U Naumann, O Schenk Computational Science Series. Chapman & Hall/CRC, 2011 | 96 | 2011 |

Optimal accumulation of Jacobian matrices by elimination methods on the dual computational graph U Naumann Mathematical Programming 99 (3), 399-421, 2004 | 84 | 2004 |

Optimal Jacobian accumulation is NP-complete U Naumann Mathematical Programming 112 (2), 427-441, 2008 | 83 | 2008 |

Toward adjoinable MPI J Utke, L Hascoet, P Heimbach, C Hill, P Hovland, U Naumann 2009 IEEE International Symposium on Parallel & Distributed Processing, 1-8, 2009 | 67 | 2009 |

GPU-accelerated sparse matrix-matrix multiplication by iterative row merging F Gremse, A Hofter, LO Schwen, F Kiessling, U Naumann SIAM Journal on Scientific Computing 37 (1), C54-C71, 2015 | 66 | 2015 |

A 3-D tomographic retrieval approach with advection compensation for the air-borne limb-imager GLORIA J Ungermann, J Blank, J Lotz, K Leppkes, L Hoffmann, T Guggenmoser, ... Atmospheric Measurement Techniques 4 (11), 2509-2529, 2011 | 57 | 2011 |

A discrete adjoint model for OpenFOAM M Towara, U Naumann Procedia Computer Science 18, 429-438, 2013 | 54 | 2013 |

Automatic Differentiation: Applications, Theory, and Implementations M Bucker, G Corliss, P Hovland, U Naumann, B Norris Lecture Notes in Computational Science and Engineering 50, 2006 | 49 | 2006 |

Efficient calculation of Jacobian matrices by optimized application of the chain rule to computational graphs U Naumann Institute for Scientific Computing, Dresden, 1999 | 47 | 1999 |

A differentiation-enabled Fortran 95 compiler U Naumann, J Riehme ACM Transactions on Mathematical Software (TOMS) 31 (4), 458-474, 2005 | 46 | 2005 |

Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography F Gremse, B Theek, S Kunjachan, W Lederle, A Pardo, S Barth, ... Theranostics 4 (10), 960, 2014 | 45 | 2014 |

Towards automatic significance analysis for approximate computing V Vassiliadis, J Riehme, J Deussen, K Parasyris, CD Antonopoulos, ... 2016 IEEE/ACM International Symposium on Code Generation and Optimization …, 2016 | 42 | 2016 |

Discrete first-and second-order adjoints and automatic differentiation for the sensitivity analysis of dynamic models R Hannemann, W Marquardt, U Naumann, B Gendler Procedia Computer Science 1 (1), 297-305, 2010 | 42 | 2010 |

Interpretative adjoints for numerical simulation codes using MPI M Schanen, U Naumann, L Hascoët, J Utke Procedia Computer Science 1 (1), 1825-1833, 2010 | 40 | 2010 |