Society for Industrial and Applied Mathematics(SIAM)

By 採編典藏組. 2008

1,597 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f65040c3aa910788931c27c73006c5f3bb1e7e85

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Citations in the corpus

Pseudospectrum and Black Hole Quasinormal Mode Instability (2020, methodology): “Spectral methods provide well-adapted tools for these calculations [8, 81, 82].”
A constant-time SLAM back-end in the continuum between global mapping and submapping: application to visual stereo SLAM (2016, methodology): “sparse Cholesky decomposition (Davis 2006), inexact Newton type algorithms (Agarwal et al.”
Multidimensional Stochastic Processes as Rough Paths: Theory and Applications (2010, background): “There are many books an ODE theory such as the authorative [80]; for a concise treatment see the relevant chapters of [41].”
Split Bregman Methods and Frame Based Image Restoration (2009, background): “8) can be applied to many important problems in imaging science (and other computational areas), including discrete partial differential equation (PDE) based approaches [30, 60] and wavelet frame based ones.”
Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1 M Unknowns (2008, methodology): “The rank of A is r, the number of ‘non-zero’ singular values [15].”
A Singular Value Thresholding Algorithm for Matrix Completion (2008, background): “general form f(Y ) are available today, see [41] for a survey.”
Total Least Squares Solution of Coordinate Transformation (2007, background): “(12) such that [8], [5], [14], [ ] [ ] F l A A l e E E e ; min ; subject to: β E A e l ⋅ − = + ) ( A l (13) where F H denotes the Frobenius norm of an n×m matrix H, which is defined by”
A Krylov–Schur approach to the truncated SVD (2012, methodology): “It is well known that a loss of orthogonality can occur when the algorithm progresses, see [24, 22].”
Simulation-based optimal Bayesian experimental design for nonlinear systems (2011, background): “For nonlinear models, however, exact evaluation of optimal design criteria is much more challenging.”
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems (2016, methodology): “This leads us to formulate the choice of basis functions as a problem in optimal experimental design [Pukelsheim, 2006].”