RAIN-FIT: Learning of Fitting Surfaces and Noise Distribution from Large Data Sets

ArXi:2604.03491v1 Announce Type: cross This paper proposes a method for estimating a surface that contains a given set of points from noisy measurements. precisely, by assuming that the surface is described by the zero set of a function in the span of a given set of features and a parametric description of the distribution of the noise, a computationally efficient method is described that estimates both the surface and the noise distribution parameters. In the provided examples, polynomial and sinusoidal basis functions were used.