Pages that link to "Item:Q1979925"
From MaRDI portal
The following pages link to Spectral convergence of graph Laplacian and heat kernel reconstruction in \(L^\infty\) from random samples (Q1979925):
Displaying 18 items.
- Wave-shape oscillatory model for nonstationary periodic time series analysis (Q2072625) (← links)
- Data-driven efficient solvers for Langevin dynamics on manifold in high dimensions (Q2105115) (← links)
- Improved spectral convergence rates for graph Laplacians on \(\varepsilon \)-graphs and \(k\)-NN graphs (Q2155800) (← links)
- Airflow recovery from thoracic and abdominal movements using synchrosqueezing transform and locally stationary Gaussian process regression (Q2157494) (← links)
- Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation (Q2168682) (← links)
- Error estimates for spectral convergence of the graph Laplacian on random geometric graphs toward the Laplace-Beltrami operator (Q2194775) (← links)
- Spectral convergence of the connection Laplacian from random samples (Q4603718) (← links)
- Convergence of Laplacian Spectra from Random Samples (Q4984202) (← links)
- (Q5053174) (← links)
- (Q5053269) (← links)
- Clustering Dynamics on Graphs: From Spectral Clustering to Mean Shift Through Fokker–Planck Interpolation (Q5054577) (← links)
- Geometric scattering on measure spaces (Q6122637) (← links)
- Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling (Q6136229) (← links)
- Learning low-dimensional nonlinear structures from high-dimensional noisy data: an integral operator approach (Q6183757) (← links)
- Spatiotemporal analysis using Riemannian composition of diffusion operators (Q6185681) (← links)
- Solving PDEs on unknown manifolds with machine learning (Q6499004) (← links)
- Kernel two-sample tests for manifold data (Q6589563) (← links)
- Non-parametric manifold learning (Q6635576) (← links)
