3 papers
stat.ME2025
Spatially Regularized Gaussian Mixtures for Clustering Spatial Transcriptomic Data
Andrea Sottosanti, Davide Risso, Francesco Denti
Spatial transcriptomics measures the expression of thousands of genes in a tissue sample while preserving its spatial structure. This class of technologies has enabled the investig…
stat.ME2024
Unguided structure learning of DAGs for count data
Thi Kim Hue Nguyen, Monica Chiogna, Davide Risso
Mainly motivated by the problem of modelling directional dependence relationships for multivariate count data in high-dimensional settings, we present a new algorithm, called learn…
stat.ME2023
Structured factorization for single-cell gene expression data
Antonio Canale, Luisa Galtarossa, Davide Risso +2
Single-cell gene expression data are often characterized by large matrices, where the number of cells may be lower than the number of genes of interest. Factorization models have e…