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“Computational Mathematics, Algorithms, and Data Processing” of MDPI consists of articles on new mathematical tools and numerical methods for computational problems. Topics covered include: numerical stability, interpolation, approximation, complexity, numerical linear algebra, differential equations (ordinary, partial), optimization, integral equations, systems of nonlinear equations, compression or distillation, and active learning.

Research & information: general --- Mathematics & science --- interpolation --- constraints --- embedded constraints --- generalized multiscale finite element method --- multiscale model reduction --- deep learning --- Deep Neural Nets --- ReLU Networks --- Approximation Theory --- radial basis functions --- native spaces --- truncated function --- approximation --- surface modeling --- second order initial value problems --- linear multistep methods --- Obrechkoff schemes --- trigonometrically fitted --- Darcy-Forchheimer model --- flow in porous media --- nonlinear equation --- heterogeneous media --- finite element method --- multiscale method --- mixed generalized multiscale finite element method --- multiscale basis functions --- two-dimensional domain --- Thiele-like rational interpolation continued fractions with parameters --- unattainable point --- inverse difference --- virtual point --- polynomial chaos --- Szegő polynomials --- directional statistics --- Rogers-Szegő --- state estimation --- clustering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

“Computational Mathematics, Algorithms, and Data Processing” of MDPI consists of articles on new mathematical tools and numerical methods for computational problems. Topics covered include: numerical stability, interpolation, approximation, complexity, numerical linear algebra, differential equations (ordinary, partial), optimization, integral equations, systems of nonlinear equations, compression or distillation, and active learning.

Research & information: general --- Mathematics & science --- interpolation --- constraints --- embedded constraints --- generalized multiscale finite element method --- multiscale model reduction --- deep learning --- Deep Neural Nets --- ReLU Networks --- Approximation Theory --- radial basis functions --- native spaces --- truncated function --- approximation --- surface modeling --- second order initial value problems --- linear multistep methods --- Obrechkoff schemes --- trigonometrically fitted --- Darcy-Forchheimer model --- flow in porous media --- nonlinear equation --- heterogeneous media --- finite element method --- multiscale method --- mixed generalized multiscale finite element method --- multiscale basis functions --- two-dimensional domain --- Thiele-like rational interpolation continued fractions with parameters --- unattainable point --- inverse difference --- virtual point --- polynomial chaos --- Szegő polynomials --- directional statistics --- Rogers-Szegő --- state estimation --- clustering --- interpolation --- constraints --- embedded constraints --- generalized multiscale finite element method --- multiscale model reduction --- deep learning --- Deep Neural Nets --- ReLU Networks --- Approximation Theory --- radial basis functions --- native spaces --- truncated function --- approximation --- surface modeling --- second order initial value problems --- linear multistep methods --- Obrechkoff schemes --- trigonometrically fitted --- Darcy-Forchheimer model --- flow in porous media --- nonlinear equation --- heterogeneous media --- finite element method --- multiscale method --- mixed generalized multiscale finite element method --- multiscale basis functions --- two-dimensional domain --- Thiele-like rational interpolation continued fractions with parameters --- unattainable point --- inverse difference --- virtual point --- polynomial chaos --- Szegő polynomials --- directional statistics --- Rogers-Szegő --- state estimation --- clustering