Synthesis Method for Manifold-Coupled Multiplexers

These functions have a simple geometric interpretation in terms of the moment map and they are real algebraic, in the sense that they are regular functions when M is regarded as a

In this work, we have shown a new way to characterize a manifold by extracting a local chart at each data point based on the unsupervised feature mapping built with a deep

For this application, the template functions obtained by the Robust Manifold Estimator based on our algorithm seem to capture the salient features of the sample of hip and knee

Section 1 provides Riemannian versions of 3 classical results of geomet- ric measure theory: Allard’s regularity theorem, the link between first variation and mean curvature in the

Keywords: Riemannian manifold, gradient flow, steepest descent, convex- ity, minimization.. AMS Subject Classification:

Formal B-series like those previously used to ana- lyze highly-oscillatory systems or to construct modified equations are employed here to construct expansions of the change

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Since the original Euclidean distance is not suit for complex manifold data structure, we design a manifold similarity measurement and proposed a K-AP clustering algorithm based