Interpolating implicit surfaces from scattered surface data using compactly supported radial basis functions

By Bryan S. Morse, Terry S. Yoo, Penny Rheingans, David T. Chen, Kalpathi R. Subramanian. Proceedings International Conference on Shape Modeling and Applications, 2001

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Radial basis functions and level set method for structural topology optimization (2006, methodology): “[55], or knot, which can be expressed as follows:”
Interpolating and approximating implicit surfaces from polygon soup (2004, methodology): “Different, locally supported functions were used in both [Muraki, 1991], [Morse et al., 2001], and [Ohtake et al.”
An 88-line MATLAB code for the parameterized level set method based topology optimization using radial basis functions (2018, background): “…positioned at the i th knot changed with the pseudo time t , and p ( x , t ), which is not necessary for some RBFs, a first-degree polynomial changed with time to account for the linear and constant portion of ϕ ( x , t ) and to ensure positive definiteness of the solution (Morse et al. 2001).”
Modelling with implicit surfaces that interpolate (2002, methodology): “We are pleased that other researchers, notably the authors of [19, 6], have begun to address this issue of computational complexity.”