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title:(Geometrically AND Enriched AND Latent AND Spaces)
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Preprint article
Geometrically Enriched Latent Spaces
A common assumption in generative models is that the generator immerses the
latent space into a Euclidean ambient space. Instead, we consider the ambient
space to be a Riemannian manifold, which allows for encoding domain knowledge
through the associated Riemannian metric. Shortest paths can
Year: 2020
Language: Undetermined
2
Book chapter
Geometrically Enriched Latent Spaces
A common assumption in generative models is that the generator immerses the latent space into a Euclidean ambient space. Instead, we consider the ambient space to be a Riemannian manifold, which allows for encoding domain knowledge through the associated Riemannian metric. Shortest paths can
Year: 2021
Language: English
