The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables ...
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
In this study we use a fast Fourier spectral technique to simulate the Navier-Stokes equations with no-slip boundary conditions. This is enforced by an immersed boundary technique ...
G. H. Keetels, H. J. H. Clercx, G. J. F. van Heijs...
Registration of 3D surfaces is a critical step for shape analysis. Recent studies show that spectral representations based on intrinsic pairwise geodesic distances between points ...
Xiuwen Liu, Arturo Donate, Matthew Jemison, Washin...
Abstract— This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is increm...
Christoffer Valgren, Tom Duckett, Achim J. Lilient...