Unsupervised learning with contrastive latent variable models

Understand

In unsupervised learning, dimensionality reduction is an important tool for data exploration and visualization.

• Because these aims are typically open-ended, it can be useful to frame the problem as looking for patterns that are enriched in one dataset relative to another.
• These pairs of datasets occur commonly, for instance a population of interest vs.
• control or signal vs.