We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...
In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of "sharpness" and the joint registration-segmentation o...
B. T. Thomas Yeo, Mert R. Sabuncu, Rahul Desikan, ...
This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of d...
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...