1 code implementation • 16 Jun 2020 • Tim Dockhorn, James A. Ritchie, Yao-Liang Yu, Iain Murray
Density deconvolution is the task of estimating a probability density function given only noise-corrupted samples.
1 code implementation • 26 Nov 2019 • James A. Ritchie, Iain Murray
The Extreme Deconvolution method fits a probability density to a dataset where each observation has Gaussian noise added with a known sample-specific covariance, originally intended for use with astronomical datasets.