Replicability, the ability to replicate scientific findings, is a prerequisite for scientific discovery
and clinical utility. Troublingly, we are in the midst of a replicability crisis. A key to …

Introduction Risk stratification of patients with COVID-19 can be fundamental to support
clinical decision-making and optimize resources. The objective of our study is to identify …

The K-sample testing problem involves determining whether K groups of data points are
each drawn from the same distribution. Analysis of variance is arguably the most classical …

Reproducibility, the ability to replicate analytical findings, is a prerequisite for both scientific
discovery and clinical utility. Troublingly, we are in the midst of a reproducibility crisis, in …

The cost of data acquisition and analysis is becoming prohibitively expensive for many
research groups across disciplines. And yet, as more data are available, more researchers …

Geodesic distance is the shortest path between two points in a Riemannian manifold.
Manifold learning algorithms, such as Isomap, seek to learn a manifold that preserves …

In this paper, we propose a novel kind of kernel, random forest kernel, to enhance the
empirical performance of MMD GAN. Different from common forests with deterministic …