2 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2020★ 1 cited
Density Deconvolution with Normalizing Flows
Tim Dockhorn, James A. Ritchie, Yaoliang Yu +1
Density deconvolution is the task of estimating a probability density function given only noise-corrupted samples. We can fit a Gaussian mixture model to the underlying density by…
stat.ML2019★ 2 cited
Scalable Extreme Deconvolution
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 intende…