2 papers
cs.LG2026
Uncertainty-Aware Deep Learning for Genomics Applications: Insights from an Empirical Study
Sepideh Saran, Mahsa Ghanbari, Uwe Ohler
Deep learning models have emerged as the standard computational tool for a wide range of applications in genomics. Yet, uncertainty quantification (UQ) -- and more specifically, th…
stat.ME2016
The Distance Precision Matrix: computing networks from nonlinear relationships
Mahsa Ghanbari, Julia Lasserre, Martin Vingron
A fundamental method of reconstructing networks, e.g. in the context of gene regulation, relies on the precision matrix (the inverse of the variance-covariance matrix) as an indica…