2.2k citations · 4k across the 42 of their papers we have counts for
9 papers · 1 filter
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
Sílvia Casacuberta, Esra Suel, Seth Flaxman
In this paper we introduce a new problem within the growing literature of interpretability for convolution neural networks (CNNs). While previous work has focused on the question o…
COVID-19-Associated Orphanhood and Caregiver Death in the United States
Susan D. Hillis, Alexandra Blenkinsop, Andrés Villaveces +12
Background: Most COVID-19 deaths occur among adults, not children, and attention has focused on mitigating COVID-19 burden among adults. However, a tragic consequence of adult deat…
Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes
James A. Scott, Axel Gandy, Swapnil Mishra +4
This article introduces epidemia, an R package for Bayesian, regression-oriented modeling of infectious diseases. The implemented models define a likelihood for all observed data w…
PriorVAE: Encoding spatial priors with VAEs for small-area estimation
Elizaveta Semenova, Yidan Xu, Adam Howes +4
Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical m…
Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out
Mélodie Monod, Alexandra Blenkinsop, Andrea Brizzi +7
The COVID-19 pandemic has caused severe public health consequences in the United States. In this study, we use a hierarchical Bayesian model to estimate the age-specific COVID-19 a…
Unrepresentative Big Surveys Significantly Overestimate US Vaccine Uptake
Valerie C. Bradley, Shiro Kuriwaki, Michael Isakov +3
Surveys are a crucial tool for understanding public opinion and behavior, and their accuracy depends on maintaining statistical representativeness of their target populations by mi…