Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29526
Abstract: To develop a manifold learning‐based method that leverages the intrinsic low‐dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification. read more here.
Keywords: spectral quantification; manifold learning; joint spectral; spectroscopic imaging ... See more keywords
A regularized approach for supervised multi-view multi-manifold learning from unlabeled data
Sign Up to like & getrecommendations! Published in 2019 at "Applied Intelligence"
DOI: 10.1007/s10489-019-01411-w
Abstract: In this paper, we combined two steps in a new multi-view multi-manifold learning algorithm that are essential for recognition tasks in the absence of class label information; first, we emphasize the first step of graph-based… read more here.
Keywords: multi view; manifold learning; view multi; multi manifold ... See more keywords
Fault feature enhancement for rotating machinery based on quality factor analysis and manifold learning
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Intelligent Manufacturing"
DOI: 10.1007/s10845-015-1125-6
Abstract: This paper explores an improved time-frequency signature to enhance the periodic transient shocks of the signal, called impulse-enhanced signature (IES) for identifying rotating machine faults. IES is extracted in the following steps: first, phase space… read more here.
Keywords: fault; space; manifold learning; quality factor ... See more keywords
Nonlinear Shape-Manifold Learning Approach: Concepts, Tools and Applications
Sign Up to like & getrecommendations! Published in 2017 at "Archives of Computational Methods in Engineering"
DOI: 10.1007/s11831-016-9189-9
Abstract: In this paper, we present the concept of a “shape manifold” designed for reduced order representation of complex “shapes” encountered in mechanical problems, such as design optimization, springback or image correlation. The overall idea is… read more here.
Keywords: learning approach; shape; manifold learning; nonlinear shape ... See more keywords
Ricci curvature and the manifold learning problem
Sign Up to like & getrecommendations! Published in 2019 at "Advances in Mathematics"
DOI: 10.1016/j.aim.2018.11.001
Abstract: Consider a sample of $n$ points taken i.i.d from a submanifold $\Sigma$ of Euclidean space. We show that there is a way to estimate the Ricci curvature of $\Sigma$ with respect to the induced metric… read more here.
Keywords: ricci curvature; learning problem; curvature manifold; manifold learning ... See more keywords
Complex scale feature extraction for gearbox via adaptive multi-mode manifold learning
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2020.108688
Abstract: Abstract The transient impacts with sideband modulation caused by some fault of gearbox are the technical basis for fault diagnosis, which will be inevitably interfered by heavy background noise distributed in complex modulation frequency bands.… read more here.
Keywords: mode; multi; method; manifold learning ... See more keywords
Multi-view clustering by joint manifold learning and tensor nuclear norm
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.11.014
Abstract: Abstract In real-world applications, the variation between multi-view data points, which should belong to the same cluster, is larger than the variation between data points belonging to different clusters. This results in instability of most… read more here.
Keywords: similarity; view; tensor; multi view ... See more keywords
Multi-task manifold learning for small sample size datasets
Sign Up to like & getrecommendations! Published in 2022 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.11.043
Abstract: In this study, we develop a method for multi-task manifold learning. The method aims to improve the performance of manifold learning for multiple tasks, particularly when each task has a small number of samples. Furthermore,… read more here.
Keywords: multi task; manifold learning; task manifold; transfer ... See more keywords
Connecting Vibrational Spectroscopy to Atomic Structure via Supervised Manifold Learning: Beyond Peak Analysis
Sign Up to like & getrecommendations! Published in 2023 at "Chemistry of Materials"
DOI: 10.1021/acs.chemmater.2c03207
Abstract: Vibrational spectroscopy is a nondestructive technique commonly used in chemical and physical analyses to determine atomic structures and associated properties. However, the evaluation and interpretation of spectroscopic profiles based on human-identifiable peaks can be difficult… read more here.
Keywords: spectroscopy; manifold learning; peak analysis; supervised manifold ... See more keywords
Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Chemical Theory and Computation"
DOI: 10.1021/acs.jctc.2c00873
Abstract: Enhanced sampling methods are indispensable in computational chemistry and physics, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods… read more here.
Keywords: learning collective; enhanced sampling; reweighted manifold; manifold learning ... See more keywords
Quantification of metabolic niche occupancy dynamics in a Baltic Sea bacterial community
Sign Up to like & getrecommendations! Published in 2022 at "mSystems"
DOI: 10.1101/2022.08.08.502896
Abstract: ABSTRACT Progress in molecular methods has enabled the monitoring of bacterial populations in time. Nevertheless, understanding community dynamics and its links with ecosystem functioning remains challenging due to the tremendous diversity of microorganisms. Conceptual frameworks… read more here.
Keywords: time; baltic sea; manifold learning; bacterial communities ... See more keywords