Add to ORKGIn this article we present a new approach for automatic adjoint differentiation (AAD) with a special focus on computations where derivatives ∂F(X) ∂X are required for multiple instances of vectors X. In practice, the presented approach is able to calculate all the differentials faster than the primal (original) C++ program for F.publishe
International audienceAlgorithmic Differentiation (AD) provides the analytic derivatives of function...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
Current implementations of automatic differentiation are far from automatic. We survey the difficult...
This dissertation is concerned with algorithmic differentiation (AD), which is a method for algorith...
International audienceWe present Automatic Differentiation (AD),a technique to obtain derivatives of...
Mit Hilfe der Technik des Automatischen Differenzierens (AD) lassen sich für Funktionen, die als Pro...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
Algorithmic Differentiation Through Automatic Graph Elimination Ordering (ADTAGEO) is based on the p...
The C++ package ADOL-C described in this paper facilitates the evaluation of first and higher deriva...
Current implementations of automatic differentiation are far from automatic. We survey the difficult...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machin...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
AbstractAlgorithmic differentiation (AD) is a mathematical concept which evolved over the last decad...
International audienceAlgorithmic Differentiation (AD) provides the analytic derivatives of function...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
Current implementations of automatic differentiation are far from automatic. We survey the difficult...
This dissertation is concerned with algorithmic differentiation (AD), which is a method for algorith...
International audienceWe present Automatic Differentiation (AD),a technique to obtain derivatives of...
Mit Hilfe der Technik des Automatischen Differenzierens (AD) lassen sich für Funktionen, die als Pro...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
Algorithmic Differentiation Through Automatic Graph Elimination Ordering (ADTAGEO) is based on the p...
The C++ package ADOL-C described in this paper facilitates the evaluation of first and higher deriva...
Current implementations of automatic differentiation are far from automatic. We survey the difficult...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machin...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
AbstractAlgorithmic differentiation (AD) is a mathematical concept which evolved over the last decad...
International audienceAlgorithmic Differentiation (AD) provides the analytic derivatives of function...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
Current implementations of automatic differentiation are far from automatic. We survey the difficult...