It's[0] a non-linear dimensionality reduction technique in the vein of t-SNE[1] that is very well known in the field. My two cents is that if your problem can

It's[0] a non-linear dimensionality reduction technique in the vein of t-SNE[1] that is very well known in the field. My two cents is that if your problem can be solved with something like UMAP + kNN[2], then you really shouldn't be using Deep Learning to solve it. [0] https://en.wikipedia.org/wiki/Nonlinear_dimensionality_reduction#Uniform_manifold_approximation_and_projection https://en.wikipedia.org/wiki/Nonlinear_dimensionality_reduc... [1] https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding https://en.wikipedia.org/wiki/T-distributed_stochastic_neigh... [2] https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm