Nature

Nonparametric Density Estimation Methods

The increasing diversity of scientific and engineering data has driven the development of flexible techniques for inferring probability distributions without assuming a specific parametric family.
Nature

Kernel Density Estimation Techniques and Applications

Kernel density estimation (KDE) is a versatile nonparametric approach to infer continuous probability distributions from finite samples. By superimposing smooth kernel functions—most commonly Gaussian ...
US Geological Survey

Comparison of methods for estimating density and population trends for low-density Asian bears

Authors Dana J. Morin, John Boulanger, Richard Bischof, David C. Lee, Dusit Ngoprasert, Angela K. Fuller, Bruce McLellan, Robert Steinmetz, Sandeep Sharma, Dave ...
ascopubs.org

Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning

We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using ...