AbstractA new, very simple, totally automated and powerful technique for numerical differentiation based on the computation of the derivative of a suitable filtered version of the noisy data by discrete mollification is presented. Several numerical examples of interest are also analyzed
In comparison to symbolic differentiation and numerical differencing, the chain rule based technique...
Automatic differentiation is a technique of computing the derivative of a function or a subroutine w...
summary:Automatic differentiation is an effective method for evaluating derivatives of function, whi...
AbstractA new, very simple, totally automated and powerful technique for numerical differentiation b...
AbstractAn automatic method for numerical differentiation, based on discrete mollification and the p...
AbstractThe method of numerical differentiation by discrete mollification is presented in a fully di...
Automatic differentiation --- the mechanical transformation of numeric computer programs to calculat...
The discrete mollification method is a data smoothing procedure, based on convolution, that is appro...
In this paper, we consider numerical differentiation of bivariate functions when a set of noisy data...
We review the methods and applications of automatic differentiation, a research and development acti...
Automatic differentiation—the mechanical transformation of numeric computer programs to calculate de...
This thesis is an exposition of the article Arithmetic of Differentiation by L.B Rall. It gives a ...
International audienceIn this article, we propose a multidimensional numerical differentiation metho...
Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Autom...
AbstractWe review the δ-mollification procedure for automatic fitting of surfaces defined from discr...
In comparison to symbolic differentiation and numerical differencing, the chain rule based technique...
Automatic differentiation is a technique of computing the derivative of a function or a subroutine w...
summary:Automatic differentiation is an effective method for evaluating derivatives of function, whi...
AbstractA new, very simple, totally automated and powerful technique for numerical differentiation b...
AbstractAn automatic method for numerical differentiation, based on discrete mollification and the p...
AbstractThe method of numerical differentiation by discrete mollification is presented in a fully di...
Automatic differentiation --- the mechanical transformation of numeric computer programs to calculat...
The discrete mollification method is a data smoothing procedure, based on convolution, that is appro...
In this paper, we consider numerical differentiation of bivariate functions when a set of noisy data...
We review the methods and applications of automatic differentiation, a research and development acti...
Automatic differentiation—the mechanical transformation of numeric computer programs to calculate de...
This thesis is an exposition of the article Arithmetic of Differentiation by L.B Rall. It gives a ...
International audienceIn this article, we propose a multidimensional numerical differentiation metho...
Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Autom...
AbstractWe review the δ-mollification procedure for automatic fitting of surfaces defined from discr...
In comparison to symbolic differentiation and numerical differencing, the chain rule based technique...
Automatic differentiation is a technique of computing the derivative of a function or a subroutine w...
summary:Automatic differentiation is an effective method for evaluating derivatives of function, whi...
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