Search Results for author:
Found 3 papers, 0 papers with code
Compressive Embedding and Visualization using Graphs
Visualizing high-dimensional data has been a focus in data analysis communities for decades, which has led to the design of many algorithms, some of which are now considered references (such as t-SNE for example).
Fast Eigenspace Approximation using Random Signals
We focus in this work on the estimation of the first $k$ eigenvectors of any graph Laplacian using filtering of Gaussian random signals.
Graph-based denoising for time-varying point clouds
Noisy 3D point clouds arise in many applications.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
