2 citations · 2 across the 4 of their papers we have counts for
4 papers
Zero-Inflated Bayesian Multi-Study Infinite Non-Negative Matrix Factorization
Blake Hansen, Dafne Zorzetto, Valeria Edefonti +1
Understanding the association between dietary patterns and health outcomes, such as the cancer risk, is crucial to inform public health guidelines and shaping future dietary interv…
Causal Inference for Latent Outcomes Learned with Factor Models
Jenna M. Landy, Dafne Zorzetto, Roberta De Vito +1
In many fields$\unicode{x2013}$including genomics, epidemiology, natural language processing, social and behavioral sciences, and economics$\unicode{x2013}$it is increasingly impor…
Bayesian Probit Multi-Study Non-negative Matrix Factorization for Mutational Signatures
Blake Hansen, Isabella N. Grabski, Giovanni Parmigiani +1
Mutational signatures are patterns of somatic mutations in tumor genomes that provide insights into underlying mutagenic processes and cancer origin. Developing reliable methods fo…
Missing data imputation using a truncated Gaussian infinite factor model with application to metabolomics data
Kate Finucane, Lorraine Brennan, Roberta De Vito +2
Metabolomics is the study of small molecules in biological samples. Metabolomics data are typically high-dimensional and contain highly correlated variables and frequent missing va…