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 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 ...

Achieve accurate RCS predictions for electrically large aerospace structures in minutes instead ofhours using advanced approximation techniques on standard desktop hardware. What Attendees will Learn ...

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 ...