We show that by searching over the continuous space for optimal sparsity level, we can reduce the fitting errors (generalization and specificities), and thereby ...

Groupwise registration of point sets is the fundamental step in creating statistical shape models. (SSMs). When the number of points on the sets varies across ...

Groupwise registration of point sets is the fundamental step in creating statistical shape models (SSMs). When the number of points on the sets varies ...

Abstract. Groupwise registration of point sets is the fundamental step in creating statistical shape models. (SSMs). When the number of points on the sets ...

Groupwise registration of point sets is the fundamental step in creating statistical shape models (SSMs). When the number of points on the sets varies ...

A Bayesian Approach to Sparse Model Selection in Statistical Shape Models by Ali Gooya, Christos Davatzikos, Alejandro F. Frangi published in SIAM.

Abstract. The Bayesian Lasso is constructed in the linear regression framework and applies the Gibbs sampling to estimate the regression parameters.

"A bayesian approach to sparse model selection in statistical shape models." SIAM Journal on Imaging Sciences 8.2 (2015): 858-887. File Format. TAR.GZ File.

We propose a method for analyzing data which consist of curves on multiple individuals, ie, longitudinal or functional data.

Abstract. A novel Bayesian approach to the problem of variable selection in multiple linear regression models is proposed.