Recovering manifold representations via unsupervised meta-learning

Recovering manifold representations via unsupervised meta-learning

Manifold representation learning holds great promise for theoretical understanding and characterization of deep neural networks' behaviors through the lens of geometries. However, data scarcity remains a major challenge in manifold analysis especially for data and applications with real-world c...

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Bibliographic Details
Main Authors:	Yunye Gong, Jiachen Yao, Ruyi Lian, Xiao Lin, Chao Chen, Ajay Divakaran, Yi Yao
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-01-01
Series:	Frontiers in Computer Science
Subjects:	manifold representation learning autoencoder meta-learning persistent homology data scarcity
Online Access:	https://www.frontiersin.org/articles/10.3389/fcomp.2024.1255517/full
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