Vector Diffusion Maps and the Connection Laplacian

1 February 2011

Papers citing "Vector Diffusion Maps and the Connection Laplacian"

50 / 106 papers shown

Title
Curvature Enhanced Data Augmentation for Regression Ilya Kaufman Sirot Omri Azencot 18 0 0 07 Jun 2025
Higher-Order Group Synchronization Adriana L. Duncan Joe Kileel 64 0 0 28 May 2025
Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework Mustafa Hajij Lennart Bastian Sarah Osentoski Hardik Kabaria John L. Davenport ... Joseph G. Kocheemoolayil Nastaran Shahmansouri Adrian Lew Theodore Papamarkou Tolga Birdal 45 0 0 27 May 2025
Supervised Manifold Learning for Functional Data Ruoxu Tan Yiming Zang 132 0 0 23 Mar 2025
A Survey on Computational Solutions for Reconstructing Complete Objects by Reassembling Their Fractured Parts Jiaxin Lu Yongqing Liang Huijun Han Jiacheng Hua Junfeng Jiang Xin Li Qixing Huang 3DV 137 3 0 18 Oct 2024
SRIF: Semantic Shape Registration Empowered by Diffusion-based Image Morphing and Flow Estimation Mingze Sun Chen Guo Puhua Jiang Shiwei Mao Yurun Chen Ruqi Huang 95 4 0 18 Sep 2024
Boundary Detection Algorithm Inspired by Locally Linear Embedding Pei-Cheng Kuo Nan Wu 55 0 0 26 Jun 2024
First-Order Manifold Data Augmentation for Regression Learning Ilya Kaufman Omri Azencot 52 4 0 16 Jun 2024
Bundle Neural Networks for message diffusion on graphs Jacob Bamberger Federico Barbero Xiaowen Dong Michael M. Bronstein 118 3 0 24 May 2024
Random Multi-Type Spanning Forests for Synchronization on Sparse Graphs Hugo Jaquard P. Amblard Simon Barthelmé Nicolas M Tremblay 62 1 0 28 Mar 2024
Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together? Hans Riess M. Veveakis Michael M. Zavlanos 135 2 0 05 Feb 2024
Convergence analysis of t-SNE as a gradient flow for point cloud on a manifold Seonghyeon Jeong Hau-tieng Wu 49 3 0 31 Jan 2024
Multi-Irreducible Spectral Synchronization for Robust Rotation Averaging Owen Howell Haoen Huang David Rosen 64 0 0 28 Nov 2023
Manifold learning: what, how, and why M. Meilă Hanyu Zhang 88 59 0 07 Nov 2023
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds Robert L. Peach M. Vinao-Carl Nir Grossman Michael David Emma-Jane Mallas David Sharp Paresh A. Malhotra P. Vandergheynst Adam Gosztolai 90 5 0 28 Sep 2023
Principal subbundles for dimension reduction M. Akhøj J. Benn E. Grong Stefan Sommer Xavier Pennec 80 1 0 06 Jul 2023
Structural Balance and Random Walks on Complex Networks with Complex Weights Yu Tian R. Lambiotte 50 11 0 04 Jul 2023
Data Representations' Study of Latent Image Manifolds Ilya Kaufman Omri Azencot 69 8 0 31 May 2023
Zoo Guide to Network Embedding Anthony Baptista Rubén J. Sánchez-García A. Baudot Ginestra Bianconi GNN 87 7 0 05 May 2023
Interpretable statistical representations of neural population dynamics and geometry Adam Gosztolai Robert L. Peach Alexis Arnaudon Mauricio Barahona P. Vandergheynst 78 10 0 06 Apr 2023
The G-invariant graph Laplacian E. Rosen Paulina Hoyos Xiuyuan Cheng Joe Kileel Y. Shkolnisky 52 1 0 29 Mar 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess Paolo Di Lorenzo Alejandro Ribeiro 72 11 0 20 Mar 2023
Dictionary-based Manifold Learning Hanyu Zhang Samson Koelle M. Meilă 140 1 0 01 Feb 2023
Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection Yang Yang Hongjian Sun Jialei Gong Di Yu FAtt 58 2 0 17 Nov 2022
Augmentation Invariant Manifold Learning Shulei Wang 244 1 0 01 Nov 2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Lorenzo Alejandro Ribeiro 96 14 0 26 Oct 2022
Smoothing complex-valued signals on Graphs with Monte-Carlo Hugo Jaquard Michaël Fanuel P. Amblard Rémi Bardenet Simon Barthelmé Nicolas M Tremblay 98 3 0 15 Oct 2022
Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent Kernel Thomas Gebhart GNN 58 1 0 19 Aug 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 230 19 0 17 Aug 2022
Probabilistic PolarGMM: Unsupervised Cluster Learning of Very Noisy Projection Images of Unknown Pose Supawit Chockchowwat Minh Nguyen 45 0 0 26 Jun 2022
Robust Group Synchronization via Quadratic Programming Yunpeng Shi Cole Wyeth Gilad Lerman 44 8 0 17 Jun 2022
Sheaf Neural Networks with Connection Laplacians Federico Barbero Cristian Bodnar Haitz Sáez de Ocáriz Borde Michael M. Bronstein Petar Velivcković Pietro Lio 70 43 0 17 Jun 2022
Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles N. Evangelou Felix Dietrich J. M. Bello-Rivas Alex J Yeh Rachel Stein M. Bevan Ioannis G. Kevekidis DiffM 68 5 0 30 Apr 2022
Diffusion of Information on Networked Lattices by Gossip Hans Riess Robert Ghrist 71 10 0 01 Apr 2022
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator Approach Xiucai Ding Rongkai Ma 95 9 0 28 Feb 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar Francesco Di Giovanni B. Chamberlain Pietro Lio Michael M. Bronstein 99 183 0 09 Feb 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 68 43 0 09 Feb 2022
Manifold learning via quantum dynamics Akshat Kumar M. Sarovar 64 0 0 20 Dec 2021
Inferring Manifolds From Noisy Data Using Gaussian Processes David B. Dunson Nan Wu 91 18 0 14 Oct 2021
Tangent Space and Dimension Estimation with the Wasserstein Distance Uzu Lim Harald Oberhauser Vidit Nanda 93 8 0 12 Oct 2021
Weisfeiler and Lehman Go Cellular: CW Networks Cristian Bodnar Fabrizio Frasca N. Otter Yu Guang Wang Pietro Lio Guido Montúfar M. Bronstein GNN 133 237 0 23 Jun 2021
Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 65 12 0 03 Jun 2021
$Efficient $\mathbb{Z}_2$ synchronization on $\mathbb{Z}^d$ under symmetry-preserving side information$ Efficient $\mathbb{Z}_2$ synchronization on $\mathbb{Z}^d$ under symmetry-preserving side information A. Alaoui 36 0 0 03 Jun 2021
Joint Community Detection and Rotational Synchronization via Semidefinite Programming Yifeng Fan Y. Khoo Zhizhen Zhao 58 6 0 13 May 2021
HodgeNet: Learning Spectral Geometry on Triangle Meshes Dmitriy Smirnov Justin Solomon 87 26 0 26 Apr 2021
Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data Yu-Chia Chen Weicheng Wu M. Meilă Ioannis G. Kevrekidis 59 12 0 13 Mar 2021
An extension of the angular synchronization problem to the heterogeneous setting Ning Zhang Hemant Tyagi 41 6 0 29 Dec 2020
Sheaf Neural Networks J. Hansen Thomas Gebhart GNN 48 43 0 08 Dec 2020
Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud Xiucai Ding Hau‐Tieng Wu 119 13 0 21 Nov 2020
Grassmannian diffusion maps based dimension reduction and classification for high-dimensional data K. D. Santos D. D. Giovanis Michael D. Shields DiffM 39 10 0 16 Sep 2020