Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud

21 November 2020

Papers citing "Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud"

5 / 5 papers shown

Title
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy Y. Lin Ronald R. Coifman Gal Mishne Ronen Talmon 40 2 0 28 Oct 2024
Augmentation Invariant Manifold Learning Shulei Wang 45 1 0 01 Nov 2022
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise Xiuyuan Cheng Boris Landa 33 3 0 22 Jun 2022
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator Approach Xiucai Ding Rongkai Ma 44 9 0 28 Feb 2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets Tal Shnitzer Mikhail Yurochkin Kristjan Greenewald Justin Solomon 41 6 0 03 Feb 2022