Background: Telemonitoring allows a clinician to monitor, on a daily basis, physiological
variables measured by patients at home. This provides a means to keep patients with heart …

Stein’s method compares probability distributions through the study of a class of linear
operators called Stein operators. While mainly studied in probability and used to underpin …

We propose a framework for analyzing and comparing distributions, which we use to construct
statistical tests to determine if two samples are drawn from different distributions. Our test …

The EPIC focal plane imaging spectrometers on XMM-Newton use CCDs to record the
images and spectra of celestial X-ray sources focused by the three X-ray mirrors. There is one …

We propose two statistical tests to determine if two samples are from different distributions.
Our test statistic is in both cases the distance between the means of the two samples mapped …

We propose an independence criterion based on the eigenspectrum of covariance operators
in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the …

We consider the scenario where training and test data are drawn from different distributions,
commonly referred to as sample selection bias. Most algorithms for this setting try to first …

Motivation: Many problems in data integration in bioinformatics can be posed as one common
question: Are two sets of observations generated by the same distribution? We propose a …

We investigate the training and performance of generative adversarial networks using the
Maximum Mean Discrepancy (MMD) as critic, termed MMD GANs. As our main theoretical …

Although kernel measures of independence have been widely applied in machine learning (notably
in kernel ICA), there is as yet no method to determine whether they have detected …