Alignment of vector fields on manifolds via contraction mappings
According to the manifold hypothesis, high-dimensional data can be viewed and meaningfully represented as a lower-dimensional manifold embedded in a higher dimensional feature space. Manifold learning is a part of machine learning where an intrinsic data representation is uncovered based on the mani...
Saved in:
Main Authors: | O.N. Kachan, Yu.A. Yanovich, E.N. Abramov |
---|---|
Format: | Article |
Language: | English |
Published: |
Kazan Federal University
2018-06-01
|
Series: | Учёные записки Казанского университета: Серия Физико-математические науки |
Subjects: | |
Online Access: | https://kpfu.ru/alignment-of-vector-fields-on-manifolds-via-403645.html |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Space time manifolds and contact structures
by: K. L. Duggal
Published: (1990-01-01) -
Detecting phase transitions in collective behavior using manifold's curvature
by: Kelum Gajamannage, et al.
Published: (2017-03-01) -
SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction
by: Bei Zhu, et al.
Published: (2025-02-01) -
Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
by: Buchfink, Patrick, et al.
Published: (2024-12-01) -
Locally conformal symplectic manifolds
by: Izu Vaisman
Published: (1985-01-01)