ABSTRACT
We introduce a new parameterization strategy that can be used to design algorithms simulating geometric flows on Wasserstein manifold, the probability density space equipped with optimal t...
ABSTRACT
First, we review the semi-discrete optimal transport problem and its relation to a Laguerre tessellation. Then, we propose a new method for solving the semi-discrete optimal transpor...
ABSTRACT
Machine Learning (ML) is a scientific study of numerical algorithms and statistical models that computer systems use to effectively predict a specific task without using specific human ins...
ABSTRACT
We propose a general method to identify nonlinear Fokker-Planck-Kolmogorov equations (FPK equations) as gradient flows on the space of Borel probability measures on Rd with a natural ...
ABSTRACT
We characterize the Bonnet surfaces with the single requirement that the mean curvature H of a surface in R^3 admit a reduction to an ordinary differential equation which possesses the Pai...
ABSTRACT
We characterize the Bonnet surfaces with the single requirement that the mean curvature H of a surface in R^3 admit a reduction to an ordinary differential equation which possesses the Pai...
ABSTRACT
Recent advances in the nonconforming FEM approximation of elliptic PDE eigenvalue problems include the guaranteed lower eigenvalue bounds (GLB) and its adaptive finite element computation....