All Papers

Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization

103

30 Oct 2025

02 Oct 2025

Spectral Self-supervised Feature Selection

Daniel Segal

Ofir Lindenbaum

Ariel Jaffe

328

12 Jul 2024

Landmark Alternating Diffusion

105

29 Apr 2024

Implicit Gaussian process representation of vector fields over arbitrary latent manifoldsInternational Conference on Learning Representations (ICLR), 2023

226

28 Sep 2023

Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and BackIEEE Transactions on Signal Processing (IEEE TSP), 2023

Claudio Battiloro

Zhiyang Wang

Hans Riess

Paolo Di Lorenzo

Alejandro Ribeiro

182

20 Mar 2023

Consistency of Fractional Graph-Laplacian Regularization in Semi-Supervised Learning with Finite LabelsSIAM Journal on Mathematical Analysis (SIAM J. Math. Anal.), 2023

Adrien Weihs

217

14 Mar 2023

Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and BackIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022

Claudio Battiloro

Zhiyang Wang

Hans Riess

P. Lorenzo

Alejandro Ribeiro

249

26 Oct 2022

Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noiseInformation and Inference A Journal of the IMA (JIII), 2022

Boris Landa

291

22 Jun 2022

SpecNet2: Orthogonalization-free spectral embedding by neural networksMathematical and Scientific Machine Learning (MSML), 2022

Ziyu Chen

Yingzhou Li

125

14 Jun 2022

Understanding the Generalization Performance of Spectral Clustering AlgorithmsAAAI Conference on Artificial Intelligence (AAAI), 2022

Shaojie Li

Shengqi Ouyang

Yong Liu

205

30 Apr 2022

Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator ApproachAnnals of Statistics (Ann. Stat.), 2022

Xiucai Ding

Rongkai Ma

332

28 Feb 2022

Minimax Optimal Regression over Sobolev Spaces via Laplacian Eigenmaps on Neighborhood GraphsInformation and Inference A Journal of the IMA (JIII), 2021

Alden Green

Sivaraman Balakrishnan

Robert Tibshirani

217

14 Nov 2021

Large sample spectral analysis of graph-based multi-manifold clusteringJournal of machine learning research (JMLR), 2021

Pengfei He

Chenghui Li

219

28 Jul 2021

Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolationApplied and Computational Harmonic Analysis (ACHA), 2021

Convergence of Graph Laplacian with kNN Self-tuned Kernels

236

25 Jan 2021

Parzen Window Approximation on Riemannian ManifoldPattern Recognition (Pattern Recognit.), 2020

A. Abhishek

S. Verma

101

29 Dec 2020

223

03 Nov 2020

Lipschitz regularity of graph Laplacians on random data cloudsSIAM Journal on Mathematical Analysis (SIAM J. Math. Anal.), 2020

Jeff Calder

A metric on directed graphs and Markov chains based on hitting probabilities

M. Lewicka

235

13 Jul 2020

213

25 Jun 2020

Consistency of Anchor-based Spectral ClusteringInformation and Inference A Journal of the IMA (JIII), 2020

Henry-Louis de Kergorlay

D. Higham

173

24 Jun 2020

Construction and Monte Carlo estimation of wavelet frames generated by a reproducing kernel

213

17 Jun 2020

Data-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions

Yuan Gao

Jiang Liu

322

22 May 2020

The SPDE Approach to Matérn Fields: Graph RepresentationsStatistical Science (Statist. Sci.), 2020

D. Sanz-Alonso

Ruiyi Yang

288

16 Apr 2020

The Spectral Underpinning of word2vecFrontiers in Applied Mathematics and Statistics (FAMS), 2020

268

27 Feb 2020

Scalability and robustness of spectral embedding: landmark diffusion is all you needInformation and Inference A Journal of the IMA (JIII), 2020

Chao Shen

Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in

305

03 Jan 2020

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

L^\infty

439

11 Dec 2019

Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs

Jeff Calder

PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds

245

29 Oct 2019

Oliver M. Crook

Tim Hurst

Carola-Bibiane Schönlieb

Unsupervised Co-Learning on

K. Zygalakis

3DPC

145

23 Sep 2019

$Unsupervised Co-Learning on $\mathcal{G}$-Manifolds Across Irreducible Representations$

\mathcal{G}

-Manifolds Across Irreducible RepresentationsNeural Information Processing Systems (NeurIPS), 2019

Yifeng Fan

When Locally Linear Embedding Hits Boundary

Zhizhen Zhao

209

06 Jun 2019

Learning by Unsupervised Nonlinear Diffusion

219

11 Nov 2018

Mauro Maggioni

James M. Murphy

DiffM

224

15 Oct 2018

Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral ClusteringFoundations of Computational Mathematics (FoCM), 2018

Shuyang Ling

Thomas Strohmer

221

29 Jun 2018

On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding

Daniel Ting

Sai Li

120

06 Mar 2018

Error estimates for spectral convergence of the graph Laplacian on random geometric graphs towards the Laplace--Beltrami operator

On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms

Moritz Gerlach

Matthias Hein

D. Slepčev

179

189

30 Jan 2018

-Laplacian Regularization in Semi-Supervised Learning

Zachary T. Kaplan

Thabo Samakhoana

D. Sanz-Alonso

191

20 Oct 2017

Analysis of

p

D. Slepčev

Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding

185

123

19 Jul 2017

180

12 Mar 2017

Efficient fetal-maternal ECG signal separation from two channel maternal abdominal ECG via diffusion-based channel selectionFrontiers in Physiology (Front. Physiol.), 2017

Ruilin Li

Martin G Frasch

Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment

185

07 Feb 2017

128

13 Jan 2017

The Geometry of Synchronization Problems and Learning Group Actions

J. Brodzki

S. Mukherjee

339

28 Oct 2016

Variational limits of k-NN graph based functionals on data cloudsSIAM Journal on Mathematics of Data Science (SIMODS), 2016

Consistency of modularity clustering on random geometric graphs

270

03 Jul 2016

A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution FrameletsSIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2016

226

04 Jun 2016

Erik Davis

S. Sethuraman

129

13 Apr 2016

The Diffusion Geometry of Fibre Bundles: Horizontal Diffusion Maps

Latent common manifold learning with alternating diffusion: analysis and applications

340

07 Feb 2016

Ronen Talmon

Spectral Convergence Rate of Graph Laplacian

MedIm

251

30 Jan 2016

Xu Wang

105

27 Oct 2015

106

22 Sep 2015

A variational approach to the consistency of spectral clusteringApplied and Computational Harmonic Analysis (ACHA), 2015

Hypoelliptic Diffusion Maps I: Tangent Bundles

D. Slepčev

170

133

08 Aug 2015

Higher-Order Regularization Learning on Hypergraphs

17 Mar 2015

Ricci Curvature and the Manifold Learning ProblemAdvances in Mathematics (Adv. Math.), 2014

Antonio G. Ache

M. Warren

232

13 Oct 2014

Title
Higher-Order Regularization Learning on Hypergraphs Adrien Weihs Andrea Bertozzi Matthew Thorpe 103 1 0 30 Oct 2025
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization Dhruv Kohli Sawyer Robertson Gal Mishne A. Cloninger 99 0 0 02 Oct 2025
Spectral Self-supervised Feature Selection Daniel Segal Ofir Lindenbaum Ariel Jaffe 328 0 0 12 Jul 2024
Landmark Alternating Diffusion Sing-Yuan Yeh Hau-tieng Wu Ronen Talmon Mao-Pei Tsui 105 1 0 29 Apr 2024
Implicit Gaussian process representation of vector fields over arbitrary latent manifoldsInternational Conference on Learning Representations (ICLR), 2023 Robert L. Peach M. Vinao-Carl Nir Grossman Michael David Emma-Jane Mallas David Sharp Paresh A. Malhotra P. Vandergheynst Adam Gosztolai 226 7 0 28 Sep 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and BackIEEE Transactions on Signal Processing (IEEE TSP), 2023 Claudio Battiloro Zhiyang Wang Hans Riess Paolo Di Lorenzo Alejandro Ribeiro 182 16 0 20 Mar 2023
Consistency of Fractional Graph-Laplacian Regularization in Semi-Supervised Learning with Finite LabelsSIAM Journal on Mathematical Analysis (SIAM J. Math. Anal.), 2023 Adrien Weihs Matthew Thorpe 217 5 0 14 Mar 2023
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and BackIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022 Claudio Battiloro Zhiyang Wang Hans Riess P. Lorenzo Alejandro Ribeiro 249 15 0 26 Oct 2022
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noiseInformation and Inference A Journal of the IMA (JIII), 2022 Xiuyuan Cheng Boris Landa 291 6 0 22 Jun 2022
SpecNet2: Orthogonalization-free spectral embedding by neural networksMathematical and Scientific Machine Learning (MSML), 2022 Ziyu Chen Yingzhou Li Xiuyuan Cheng 125 7 0 14 Jun 2022
Understanding the Generalization Performance of Spectral Clustering AlgorithmsAAAI Conference on Artificial Intelligence (AAAI), 2022 Shaojie Li Shengqi Ouyang Yong Liu 205 4 0 30 Apr 2022
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator ApproachAnnals of Statistics (Ann. Stat.), 2022 Xiucai Ding Rongkai Ma 332 12 0 28 Feb 2022
Minimax Optimal Regression over Sobolev Spaces via Laplacian Eigenmaps on Neighborhood GraphsInformation and Inference A Journal of the IMA (JIII), 2021 Alden Green Sivaraman Balakrishnan Robert Tibshirani 217 12 0 14 Nov 2021
Large sample spectral analysis of graph-based multi-manifold clusteringJournal of machine learning research (JMLR), 2021 Nicolas García Trillos Pengfei He Chenghui Li 219 11 0 28 Jul 2021
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolationApplied and Computational Harmonic Analysis (ACHA), 2021 Xiuyuan Cheng Nan Wu 236 30 0 25 Jan 2021
Parzen Window Approximation on Riemannian ManifoldPattern Recognition (Pattern Recognit.), 2020 A. Abhishek S. Verma 101 2 0 29 Dec 2020
Convergence of Graph Laplacian with kNN Self-tuned Kernels Xiuyuan Cheng Hau‐Tieng Wu 223 26 0 03 Nov 2020
Lipschitz regularity of graph Laplacians on random data cloudsSIAM Journal on Mathematical Analysis (SIAM J. Math. Anal.), 2020 Jeff Calder Nicolas García Trillos M. Lewicka 235 38 0 13 Jul 2020
A metric on directed graphs and Markov chains based on hitting probabilities Z. Boyd Nicolas Fraiman J. Marzuola P. Mucha Braxton Osting Jonathan Weare 213 9 0 25 Jun 2020
Consistency of Anchor-based Spectral ClusteringInformation and Inference A Journal of the IMA (JIII), 2020 Henry-Louis de Kergorlay D. Higham 173 6 0 24 Jun 2020
Construction and Monte Carlo estimation of wavelet frames generated by a reproducing kernel Ernesto De Vito Ž. Kereta Valeriya Naumova Lorenzo Rosasco Stefano Vigogna 213 3 0 17 Jun 2020
Data-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions Yuan Gao Jiang Liu Nan Wu 322 13 0 22 May 2020
The SPDE Approach to Matérn Fields: Graph RepresentationsStatistical Science (Statist. Sci.), 2020 D. Sanz-Alonso Ruiyi Yang 288 21 0 16 Apr 2020
The Spectral Underpinning of word2vecFrontiers in Applied Mathematics and Statistics (FAMS), 2020 Ariel Jaffe Y. Kluger Ofir Lindenbaum J. Patsenker Erez Peterfreund Stefan Steinerberger 268 8 0 27 Feb 2020
Scalability and robustness of spectral embedding: landmark diffusion is all you needInformation and Inference A Journal of the IMA (JIII), 2020 Chao Shen Hau‐Tieng Wu 305 31 0 03 Jan 2020
$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 David B. Dunson Hau‐Tieng Wu Nan Wu 439 72 0 11 Dec 2019
Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs Jeff Calder Nicolas García Trillos 245 40 0 29 Oct 2019
PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds Oliver M. Crook Tim Hurst Carola-Bibiane Schönlieb Matthew Thorpe K. Zygalakis 3DPC 145 2 0 23 Sep 2019
$Unsupervised Co-Learning on $\mathcal{G}$-Manifolds Across Irreducible Representations$ Unsupervised Co-Learning on $\mathcal{G}$ -Manifolds Across Irreducible RepresentationsNeural Information Processing Systems (NeurIPS), 2019 Yifeng Fan Tingran Gao Zhizhen Zhao 209 6 0 06 Jun 2019
When Locally Linear Embedding Hits Boundary Hau‐Tieng Wu Nan Wu 219 11 0 11 Nov 2018
Learning by Unsupervised Nonlinear Diffusion Mauro Maggioni James M. Murphy DiffM 224 42 0 15 Oct 2018
Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral ClusteringFoundations of Computational Mathematics (FoCM), 2018 Shuyang Ling Thomas Strohmer 221 20 0 29 Jun 2018
On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding Daniel Ting Sai Li 120 8 0 06 Mar 2018
Error estimates for spectral convergence of the graph Laplacian on random geometric graphs towards the Laplace--Beltrami operator Nicolas García Trillos Moritz Gerlach Matthias Hein D. Slepčev 179 189 0 30 Jan 2018
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms Nicolas García Trillos Zachary T. Kaplan Thabo Samakhoana D. Sanz-Alonso 191 22 0 20 Oct 2017
Analysis of $p$ -Laplacian Regularization in Semi-Supervised Learning D. Slepčev Matthew Thorpe 185 123 0 19 Jul 2017
Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding Hau‐Tieng Wu Nan Wu 180 41 0 12 Mar 2017
Efficient fetal-maternal ECG signal separation from two channel maternal abdominal ECG via diffusion-based channel selectionFrontiers in Physiology (Front. Physiol.), 2017 Ruilin Li Martin G Frasch Hau‐Tieng Wu 185 47 0 07 Feb 2017
Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment Ori Katz Ronen Talmon Y. Lo Hau‐Tieng Wu 128 4 0 13 Jan 2017
The Geometry of Synchronization Problems and Learning Group Actions Tingran Gao J. Brodzki S. Mukherjee 339 38 0 28 Oct 2016
Variational limits of k-NN graph based functionals on data cloudsSIAM Journal on Mathematics of Data Science (SIMODS), 2016 Nicolas García Trillos 270 9 0 03 Jul 2016
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution FrameletsSIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2016 Rujie Yin Tingran Gao Yue M. Lu Ingrid Daubechies 226 53 0 04 Jun 2016
Consistency of modularity clustering on random geometric graphs Erik Davis S. Sethuraman 129 19 0 13 Apr 2016
The Diffusion Geometry of Fibre Bundles: Horizontal Diffusion Maps Tingran Gao 340 21 0 07 Feb 2016
Latent common manifold learning with alternating diffusion: analysis and applications Ronen Talmon Hau‐Tieng Wu MedIm 251 45 0 30 Jan 2016
Spectral Convergence Rate of Graph Laplacian Xu Wang 105 26 0 27 Oct 2015
Harmonic Extension Zuoqiang Shi Jian Sun Minghao Tian 106 4 0 22 Sep 2015
A variational approach to the consistency of spectral clusteringApplied and Computational Harmonic Analysis (ACHA), 2015 Nicolas García Trillos D. Slepčev 170 133 0 08 Aug 2015
Hypoelliptic Diffusion Maps I: Tangent Bundles Tingran Gao 74 0 0 17 Mar 2015
Ricci Curvature and the Manifold Learning ProblemAdvances in Mathematics (Adv. Math.), 2014 Antonio G. Ache M. Warren 232 12 0 13 Oct 2014

Title

Adrien Weihs

Andrea Bertozzi