We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the...
As networks become all-pervasive the importance of efficient information gathering for purposes such as monitoring, fault diagnosis, and performance evaluation can only increase. E...
In this paper, we present 3DLoc: an integrated system of hardware and software toolkits for locating an 802.11compliant mobile device in a three dimensional (3D) space. 3DLoc feat...
Jizhi Wang, Yinjie Chen, Xinwen Fu, Jie Wang, Wei ...
We propose a novel method for axonal bouton modeling and automated detection in populations of labeled neurons, as well as bouton distribution analysis for the study of neural cir...
Abhay Mavalankar, Amina Chebira, Christina A. Hall...