Many useful algorithms for processing images and geometry fall under the general framework of high-dimensional Gaussian filtering. This family of algorithms includes bilateral ...
We propose a flexible approach for the visualization of large, high-dimensional datasets. The raw, highdimensional data is mapped into an abstract 3D distance space using the Fast...
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
In this work, we propose a new grid conversion algorithm between the hexagonal lattice and the orthogonal (a.k.a. Cartesian) lattice. The conversion process, named H2O, is easy to...
Abstract--A new grid conversion method is proposed to resample between two 2-D periodic lattices with the same sampling density. The main feature of our approach is the symmetric r...
Laurent Condat, Dimitri Van De Ville, Brigitte For...