We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
We aim to specify program transformations in a declarative style, and then to generate executable program transformers from such specifications. Many transformations require non-t...
Ganesh Sittampalam, Oege de Moor, Ken Friis Larsen
The linear deterministic model of relay channels is a generalization of the traditional directed network model which has become popular in the study of the flow of information ove...
We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary...
The modeling and analysis of large networks of autonomous agents is an important topic with applications in many different disciplines. One way of modeling the development of such...