Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Pair approximations have often been used to predict equilibrium conditions in spatially-explicit epidemiological and ecological systems. In this work, we investigate whether this ...
This paper addresses the issues of nonlinear edge-preserving image smoothing and segmentation. A ML-based approach is proposed which uses an iterative algorithm to solve the probl...
Various methods have been proposed for fitting subdivision surfaces to different forms of shape data (e.g., dense meshes or point clouds), but none of these methods effectively de...
We propose a framework for 3D geometry processing that provides direct access to surface curvature to facilitate advanced shape editing, filtering, and synthesis algorithms. The c...