Nature

Clustering single-cell RNA-seq data with a model-based deep learning approach

Single-cell RNA sequencing (scRNA-seq) promises to provide higher resolution of cellular differences than bulk RNA sequencing. Clustering transcriptomes profiled by scRNA-seq has been routinely ...
Nature

Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry

A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to ...
International Monetary Fund

UnFEAR: Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the ...