: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
The performance of multi-hop CSMA/CA networks has in most cases been evaluated via simulations, or analytically using a perfect collision channel model. Using such methods, one ca...
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component in simulation-based measurements of network observables, with applications rangi...