51 citations · 68 across the 7 of their papers we have counts for
7 papers
A Predictor-Informed Multi-Subject Bayesian Approach for Dynamic Functional Connectivity
Jaylen Lee, Sana Hussain, Ryan Warnick +6
Time Varying Functional Connectivity (TVFC) investigates how the interactions among brain regions vary over the course of an fMRI experiment. The transitions between different indi…
Multiple hypothesis screening using mixtures of non-local distributions with applications to genomic studies
Francesco Denti, Stefano Peluso, Michele Guindani +1
The analysis of large-scale datasets, especially in biomedical contexts, frequently involves a principled screening of multiple hypotheses. The celebrated two-group model jointly m…
Bayesian Time-Varying Tensor Vector Autoregressive Models for Dynamic Effective Connectivity
Wei Zhang, Ivor Cribben, sonia Petrone +1
In contemporary neuroscience, a key area of interest is dynamic effective connectivity, which is crucial for understanding the dynamic interactions and causal relationships between…
A Horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging
Francesco Denti, Ricardo Azevedo, Chelsie Lo +4
In this paper, we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy - a recently developed technique for whole-brain imaging.…
A hierarchical Bayesian model for inference of copy number variants and their association to gene expression
Alberto Cassese, Michele Guindani, Mahlet G. Tadesse +2
A number of statistical models have been successfully developed for the analysis of high-throughput data from a single source, but few methods are available for integrating data fr…
A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration
Brian J. Reich, Jo Eidsvik, Michele Guindani +2
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenab…
Generalized Species Sampling Priors with Latent Beta reinforcements
Edoardo M. Airoldi, Thiago Costa, Federico Bassetti +2
Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appro…