Dimension reduction plays a crucial role in machine learning to serve data exploration and visualization 1,2. By transforming data into an embedding space, it reveals the intrinsic structures and ...

High-dimensional data have become ubiquitous across genomics, neuroscience, finance and other domains, characterised by a number of variables that can match or exceed the number of observations.