This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
This paper focuses on the use of nuclear DNA Short Tandem Repeat traits for the identification of the victims of a Mass Fatality Incident. The goal of the analysis is the assessme...
The recent upsurge of research toward compressive sampling and parsimonious signal representations hinges on signals being sparse, either naturally, or, after projecting them on a...
Georgios B. Giannakis, Gonzalo Mateos, Shahrokh Fa...
This paper presents a method for the localization of reflectors in an acoustic environment, using robust beamforming techniques and a cylindrical microphone array, for which an i...
Edwin Mabande, Haohai Sun, Konrad Kowalczyk, Walte...