$Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples$

Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples

11 December 2019

David B. Dunson

Papers citing "Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples"

14 / 14 papers shown

Title
Implicit Manifold Gaussian Process Regression Bernardo Fichera Viacheslav Borovitskiy Andreas Krause A. Billard 18 3 0 30 Oct 2023
Representing and Learning Functions Invariant Under Crystallographic Groups Ryan P. Adams Peter Orbanz 29 4 0 08 Jun 2023
Convolutional Filtering on Sampled Manifolds Zhiyang Wang Luana Ruiz Alejandro Ribeiro 26 3 0 20 Nov 2022
Augmentation Invariant Manifold Learning Shulei Wang 45 1 0 01 Nov 2022
Convolutional Neural Networks on Manifolds: From Graphs and Back Zhiyang Wang Luana Ruiz Alejandro Ribeiro 3DPC GNN 40 14 0 01 Oct 2022
Large data limit of the MBO scheme for data clustering: convergence of the dynamics Tim Laux Jona Lelmi 40 7 0 13 Sep 2022
Geometric Scattering on Measure Spaces Joyce A. Chew M. Hirn Smita Krishnaswamy Deanna Needell Michael Perlmutter H. Steach Siddharth Viswanath Hau‐Tieng Wu GNN 42 16 0 17 Aug 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
SpecNet2: Orthogonalization-free spectral embedding by neural networks Ziyu Chen Yingzhou Li Xiuyuan Cheng 26 4 0 14 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
Lipschitz regularity of graph Laplacians on random data clouds Jeff Calder Nicolas García Trillos M. Lewicka 25 30 0 13 Jul 2020
Data-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions Yuan Gao Jiang Liu Nan Wu 21 12 0 22 May 2020
Scalability and robustness of spectral embedding: landmark diffusion is all you need Chao Shen Hau‐Tieng Wu 48 24 0 03 Jan 2020