Curvature-flow-regularized latent spaces improve mean out-of-distribution errors for Burger's equation relative to a plain autoencoder, but the flows are heuristic and the evidence is limited.
Manifold regularization: A geometric framework for learning from labeled and unlabeled examples.Journal of Machine Learning Research, 7(85):2399–2434, 2006
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Geometric flow regularization in latent spaces for smooth dynamics with the efficient variations of curvature
Curvature-flow-regularized latent spaces improve mean out-of-distribution errors for Burger's equation relative to a plain autoencoder, but the flows are heuristic and the evidence is limited.