Recovering Hidden Components in Multimodal Data with Composite Diffusion Operators

DOI10.1137/18M1218157zbMath1499.62463arXiv1808.07312OpenAlexW2977187675WikidataQ127250031 ScholiaQ127250031MaRDI QIDQ5025791

Hau-Tieng Wu, Mirela Ben Chen, Ronen Talmon, Tal Shnitzer, Leonidas J. Guibas

Publication date: 3 February 2022

Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1808.07312

zbMATH Keywords

manifold learningdiffusion mapssensor fusioncommon variablemultimodal datashape differences

Mathematics Subject Classification ID

Statistics on manifolds (62R30) Inference from stochastic processes and spectral analysis (62M15) General geometric structures on low-dimensional manifolds (57M50) Embeddings in differential topology (57R40)

Related Items (4)

A continuum limit for the PageRank algorithm ⋮ Spatiotemporal analysis using Riemannian composition of diffusion operators ⋮ Explore Intrinsic Geometry of Sleep Dynamics and Predict Sleep Stage by Unsupervised Learning Techniques ⋮ Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks

Uses Software

• EMD
• PhysioToolkit

Cites Work

• Unnamed Item
• Time coupled diffusion maps
• Learning the geometry of common latent variables using alternating-diffusion
• Wave-shape function analysis. When cepstrum meets time-frequency analysis
• The earth mover's distance as a metric for image retrieval
• Bi-stochastic kernels via asymmetric affinity functions
• Diffusion maps for changing data
• Latent common manifold learning with alternating diffusion: analysis and applications
• Magnetic eigenmaps for the visualization of directed networks
• Diffusion maps
• Diffusion maps, spectral clustering and reaction coordinates of dynamical systems
• Concerning nonnegative matrices and doubly stochastic matrices
• ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform
• Dynamic isoperimetry and the geometry of Lagrangian coherent structures
• The Wasserstein distance and approximation theorems
• Spectral convergence of the connection Laplacian from random samples
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Map-based exploration of intrinsic shape differences and variability
• Joint Manifolds for Data Fusion
• RELATIONS BETWEEN TWO SETS OF VARIATES

This page was built for publication: Recovering Hidden Components in Multimodal Data with Composite Diffusion Operators