96 citations · 97 across the 3 of their papers we have counts for
7 papers
Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic
Saskia Comess, Hannah Wang, Susan Holmes +1
Pooled testing offers an efficient solution to the unprecedented testing demands of the COVID-19 pandemic, although with potentially lower sensitivity and increased costs to implem…
A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses
Claire Donnat, Nina Miolane, Freddy Bunbury +1
Computer-Aided Diagnosis has shown stellar performance in providing accurate medical diagnoses across multiple testing modalities (medical images, electrophysiological signals, etc…
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Alice Le Brigant, Johan Mathe +16
We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matri…
Modeling the Heterogeneity in COVID-19's Reproductive Number and its Impact on Predictive Scenarios
Claire Donnat, Susan Holmes
The correct evaluation of the reproductive number for COVID-19 -- which characterizes the average number of secondary cases generated by each typical primary case -- is central…
Convex Hierarchical Clustering for Graph-Structured Data
Claire Donnat, Susan Holmes
Convex clustering is a recent stable alternative to hierarchical clustering. It formulates the recovery of progressively coalescing clusters as a regularized convex problem. While…
Constrained Bayesian ICA for Brain Connectome Inference
Claire Donnat, Leonardo Tozzi, Susan Holmes
Brain connectomics is a developing field in neurosciences which strives to understand cognitive processes and psychiatric diseases through the analysis of interactions between brai…