can be used with any operator overloading AD package replaces the manual process, which is slow and likely to overestimate the number active variables successfully identifies active variables can change the data type of active variables of most C data types In the future we would like to: gather performance data fully support C+
Automatic differentiation (AD) is a methodology for developing sensitivity-enhanced versions of arbi...
Algorithmic differentiation (AD) based on operator overloading is often the only feasible approach f...
FIXME. Automatic differentiation tools use 1 of 2 strategies to access derivative values. These stra...
Automatic Differentiation (AD) automatically performs the differentiation of models expressed in a h...
Abstract. Automatic Differentiation is the process of translating one program that computes a functi...
International audienceAs Automatic Differentiation (AD) usage is spreading to larger and more sophis...
Multiphysics software needs derivatives for, e.g., solving a system of non-linear equations, conduct...
Automatic differentiation (AD) is a methodology for developing sensitivity-enhanced versions of arbi...
Operator overloading allows the semantic extension of existing code without the need for sweeping c...
AD is a fast and comprehensive open-source C++ library for automatic differentiation by Xcelerit. It...
We present a new tool, ADIC2, for automatic differentiation (AD) of C and C++ code through source-to...
AbstractWe present a new tool, ADIC2, for automatic differentiation (AD) of C and C++ code through s...
Mit Hilfe der Technik des Automatischen Differenzierens (AD) lassen sich für Funktionen, die als Pro...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
Many applications require the derivatives of functions defined by computer programs. Automatic diffe...
Automatic differentiation (AD) is a methodology for developing sensitivity-enhanced versions of arbi...
Algorithmic differentiation (AD) based on operator overloading is often the only feasible approach f...
FIXME. Automatic differentiation tools use 1 of 2 strategies to access derivative values. These stra...
Automatic Differentiation (AD) automatically performs the differentiation of models expressed in a h...
Abstract. Automatic Differentiation is the process of translating one program that computes a functi...
International audienceAs Automatic Differentiation (AD) usage is spreading to larger and more sophis...
Multiphysics software needs derivatives for, e.g., solving a system of non-linear equations, conduct...
Automatic differentiation (AD) is a methodology for developing sensitivity-enhanced versions of arbi...
Operator overloading allows the semantic extension of existing code without the need for sweeping c...
AD is a fast and comprehensive open-source C++ library for automatic differentiation by Xcelerit. It...
We present a new tool, ADIC2, for automatic differentiation (AD) of C and C++ code through source-to...
AbstractWe present a new tool, ADIC2, for automatic differentiation (AD) of C and C++ code through s...
Mit Hilfe der Technik des Automatischen Differenzierens (AD) lassen sich für Funktionen, die als Pro...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
Many applications require the derivatives of functions defined by computer programs. Automatic diffe...
Automatic differentiation (AD) is a methodology for developing sensitivity-enhanced versions of arbi...
Algorithmic differentiation (AD) based on operator overloading is often the only feasible approach f...
FIXME. Automatic differentiation tools use 1 of 2 strategies to access derivative values. These stra...