General-purpose kernel regularization of boundary integral equations via density interpolation.
Luiz M. FariaCarlos Pérez-ArancibiaMarc BonnetPublished in: CoRR (2020)
Keyphrases
- general purpose
- reproducing kernel hilbert space
- kernel ridge regression
- kernel machines
- smoothing parameter
- kernel methods
- special purpose
- cubic convolution
- kernel function
- nonparametric density estimation
- surface interpolation
- polynomial kernels
- domain specific
- kernel matrices
- object boundaries
- density estimation
- hamilton jacobi
- programming language
- reproducing kernel
- application specific
- regularization parameter
- numerical solution
- kernel density estimator
- image interpolation
- linear interpolation
- mathematical model
- support vector
- optimal kernel
- feature space
- optimal parameter values
- density estimates
- medial axis
- interpolation methods
- markov random field
- loss function
- numerical scheme
- kernel regression
- linear equations
- parameter selection
- support vector machine
- differential equations
- density function
- kernel matrix
- kernel learning
- interpolation method
- gaussian kernels
- finite difference
- regularized least squares