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cs.LG2026
Evaluating Autoencoders for Parametric and Invertible Multidimensional Projections
Frederik L. Dennig, Nina Geyer, Daniela Blumberg +2
Recently, neural networks have gained attention for creating parametric and invertible multidimensional data projections. Parametric projections allow for embedding previously unse…
cs.LG2025
DE-VAE: Revealing Uncertainty in Parametric and Inverse Projections with Variational Autoencoders using Differential Entropy
Frederik L. Dennig, Daniel A. Keim
Recently, autoencoders (AEs) have gained interest for creating parametric and invertible projections of multidimensional data. Parametric projections make it possible to embed new,…