This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
We describe the challenge of combining continuous computer vision techniques and qualitative, symbolic methods to achieve a system capable of cognitive vision. Key to a truly cogni...
Anthony G. Cohn, David C. Hogg, Brandon Bennett, V...
A specific class of ODEs has been shown to be adequate to describe the essential features of the complex dynamics of Gene-Regulatory Networks (GRN). But, the effective exploitatio...