Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
- Two software packages for solving sparse systems of linear equations, SuperLU and UMFPACK, have been integrated with the University of Maine Ice Sheet Model for predicting the fo...
Abstract— We present and examine a technique for estimating the ego-motion of a mobile robot using memory-based learning and a monocular camera. Unlike other approaches that rely...
Richard Roberts, Hai Nguyen, Niyant Krishnamurthi,...
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...