Neural network approximation techniques have emerged as a formidable approach in computational mathematics and machine learning, providing robust tools for approximating complex functions. By ...

This work proposes a hyperspherical sparse approximation framework for detecting jump discontinuities in functions in high-dimensional spaces. The need for a novel approach results from the ...

Adaptive Fourier Decomposition and Rational Approximation Techniques represent a significant evolution in the analysis and reconstruction of signals and functions. These methods extend classical ...

The circumference of a sphere is measured to be 24 cm, with a possible error of 0.25 cm. Use the differential \(dV\) to estimate the maximum error in the calculated ...

A suite developed by a Lawrence Livermore National Laboratory (LLNL) team to simplify evaluation of approximation techniques for scientific applications has won the first-ever Best Reproducibility ...

A resource allocation algorithm proposed by Luss and Gupta is extended by the introduction of a numerical method for the optimal distribution of a continous resource among preselected activities as an ...

Dr. Doostan's research team is focused on the development of novel theories and numerical tools to rigorously tackle several grand challenges associated with Uncertainty Quantification (UQ) and ...

You are currently accessing Risk.net via your Enterprise account. If you already have an account please use the link below to sign in. If you have any problems with your access or would like to ...