AbstractIn the straight-line program model, it is known that computing all partial derivatives of a single polynomial induces only a constant increase in complexity, using the reverse derivation mode. We show that no such result holds for shifts, differences, q-shifts or q-differences
Automatic differentiation is a practical field of computational mathematics of growing interest acro...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Abstract—Derivatives of estimated static relations are often used for linearization in control and i...
AbstractIn the straight-line program model, it is known that computing all partial derivatives of a ...
We study the high order reverse mode of Automatic Differentiation (AD) in the dissertation. Automati...
Abstract. The numerical methods employed in the solution of many scientic computing problems require...
13 pages, 1 figure, arXiv:1608.00801, DOI: 10.6084/m9.figshare.4955384The main aim of this paper to ...
Abstract. The main aim of this paper to establish the relations between forward, backward and centra...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
It is shown conditions on derivatives can be expressed in a discrete manner without any requirements...
Automatic differentiation (AD) is conventionally understood as a family of distinct algorithms, root...
Abstract. We show that the problem of accumulating Jacobian matrices by using a minimal number of fl...
We study the correctness of automatic differentiation (AD) in the context of a higher-order, Turing-...
In this paper, we give a simple and efficient implementation of reverse-mode automatic differentiati...
International audienceWe study the correctness of automatic differentiation (AD) in the context of a...
Automatic differentiation is a practical field of computational mathematics of growing interest acro...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Abstract—Derivatives of estimated static relations are often used for linearization in control and i...
AbstractIn the straight-line program model, it is known that computing all partial derivatives of a ...
We study the high order reverse mode of Automatic Differentiation (AD) in the dissertation. Automati...
Abstract. The numerical methods employed in the solution of many scientic computing problems require...
13 pages, 1 figure, arXiv:1608.00801, DOI: 10.6084/m9.figshare.4955384The main aim of this paper to ...
Abstract. The main aim of this paper to establish the relations between forward, backward and centra...
The context of this work is Automatic Differentiation (AD). Fundamentally, AD transforms a program t...
It is shown conditions on derivatives can be expressed in a discrete manner without any requirements...
Automatic differentiation (AD) is conventionally understood as a family of distinct algorithms, root...
Abstract. We show that the problem of accumulating Jacobian matrices by using a minimal number of fl...
We study the correctness of automatic differentiation (AD) in the context of a higher-order, Turing-...
In this paper, we give a simple and efficient implementation of reverse-mode automatic differentiati...
International audienceWe study the correctness of automatic differentiation (AD) in the context of a...
Automatic differentiation is a practical field of computational mathematics of growing interest acro...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Abstract—Derivatives of estimated static relations are often used for linearization in control and i...
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