We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
We present a new approach to runtime verification that utilizes classical statistical techniques such as Monte Carlo simulation, hypothesis testing, and confidence interval estima...
Sean Callanan, Radu Grosu, Abhishek Rai, Scott A. ...
In an era of cooperating ad hoc networks and pervasive wireless connectivity, we are becoming more vulnerable to malicious attacks. Many of these attacks are silent in nature and ...
Anatomical shapes present a unique problem in terms of accurate representation and medical image segmentation. Three-dimensional (3D) statistical shape models have been extensivel...
Eric Berg, Mohamed Mahfouz, Christian Debrunner, W...
The promise of plentiful data on common human genetic variations has given hope that we will be able to uncover genetic factors behind common diseases that have proven difficult ...