9 citations · 14 across the 7 of their papers we have counts for
3 papers · 1 filter
On Out-of-sample Embedding in UMAP
Mohammad Tariqul Islam, Jason W. Fleischer
Neighbor embedding algorithms reveal correlations in high-dimensional data by constructing an equivalent graph representation in a lower-dimensional space. An increasingly popular…
Manifold Approximation leads to Robust Kernel Alignment
Mohammad Tariqul Islam, Du Liu, Deblina Sarkar
Centered kernel alignment (CKA) is a popular metric for comparing representations, determining equivalence of networks, and conducting neuroscience research. However, CKA does not…
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction
Mohammad Tariqul Islam, Jason W. Fleischer
Uniform manifold approximation and projection (UMAP) is among the most popular neighbor embedding methods. The method samples pairs of point indices according to similarities in th…