ArticleFrontiers in computational neuroscience2023
Toward a computational theory of manifold untangling: from global embedding to local flattening.
Article in Frontiers in computational neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Computational mechanisms transforming visual codes into sparse representations.Neuroscience and biobehavioral reviews · 2026Review
- Identifying suspicious naevi with dermoscopy via variational autoencoder auxiliary generative classifiers.Physical and engineering sciences in medicine · 2025Article
- Simple and complex cells revisited: toward a selectivity-invariance model of object recognition.Frontiers in computational neuroscience · 2023Article
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Abstract
It has been hypothesized that the ventral stream processing for object recognition is based on a mechanism called cortically local subspace untangling. A mathematical abstraction of object recognition by the visual cortex is how to untangle the manifolds associated with different object categories. Such a manifold untangling problem is closely related to the celebrated kernel trick in metric space. In this paper, we conjecture that there is a more general solution to manifold untangling in the topological space without artificially defining any distance metric. Geometrically, we can either
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