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Found 2 papers, 2 papers with code
Variational Autoencoder with Learned Latent Structure
This enables us to learn the nonlinear manifold structure from the data and use that structure to define a prior in the latent space.
Active embedding search via noisy paired comparisons
Suppose that we wish to estimate a user's preference vector $w$ from paired comparisons of the form "does user $w$ prefer item $p$ or item $q$?," where both the user and items are embedded in a low-dimensional Euclidean space with distances that reflect user and item similarities.
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