Testing the Manifold Hypothesis

1 October 2013

Papers citing "Testing the Manifold Hypothesis"

23 / 23 papers shown

Title
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling Michal Balcerak Tamaz Amiranashvili Suprosanna Shit Antonio Terpin Lea Bogensperger Sebastian Kaltenbach Petros Koumoutsakos Bjoern Menze DiffM 112 3 0 14 Apr 2025
Token embeddings violate the manifold hypothesis Michael Robinson Sourya Dey Tony Chiang 96 2 0 01 Apr 2025
Shape Modeling of Longitudinal Medical Images: From Diffeomorphic Metric Mapping to Deep Learning Edwin Tay Nazli Tümer Amir A. Zadpoor MedIm 215 0 0 27 Mar 2025
Spherical Tree-Sliced Wasserstein Distance Hoang V. Tran Thanh T. Chu K. Nguyen Trang Pham Tam Le Trung Quoc Nguyen OT 86 5 0 14 Mar 2025
Variational autoencoders with latent high-dimensional steady geometric flows for dynamics Andrew Gracyk DRL 126 1 0 03 Jan 2025
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy Ya-Wei Eileen Lin Ronald R. Coifman Zhengchao Wan Ronen Talmon 166 3 0 28 Oct 2024
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds Xingzhi Sun Danqi Liao Kincaid MacDonald Yanlei Zhang Chen Liu Guillaume Huguet Guy Wolf Ian M. Adelstein Tim G. J. Rudner Smita Krishnaswamy 80 6 0 16 Oct 2024
Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion Enrico Ventura Beatrice Achilli Gianluigi Silvestri Carlo Lucibello L. Ambrogioni DiffM 76 8 0 08 Oct 2024
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows Willem Diepeveen Georgios Batzolis Zakhar Shumaylov Carola-Bibiane Schönlieb DiffM 88 3 0 02 Oct 2024
Relative Representations: Topological and Geometric Perspectives Alejandro García-Castellanos Giovanni Luca Marchetti Danica Kragic Martina Scolamiero 81 1 0 17 Sep 2024
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation Melanie F. Pradier Javier González CML 54 0 0 09 Sep 2024
Manifold learning in Wasserstein space Keaton Hamm Caroline Moosmüller Bernhard Schmitzer Matthew Thorpe 77 5 0 14 Nov 2023
Application-driven Validation of Posteriors in Inverse Problems T. Adler Jan-Hinrich Nolke Annika Reinke M. Tizabi Sebastian Gruber ... Lynton Ardizzone Paul F. Jaeger Florian Buettner Ullrich Kothe Lena Maier-Hein MedIm 66 1 0 18 Sep 2023
Giga-scale Kernel Matrix Vector Multiplication on GPU Robert Hu Siu Lun Chau Dino Sejdinovic J. Glaunès 64 2 0 02 Feb 2022
Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach Yikun Zhang Yen-Chi Chen 115 1 0 16 Oct 2021
Variational Autoencoder with Learned Latent Structure Marissa Connor Gregory H. Canal Christopher Rozell CML DRL 58 43 0 18 Jun 2020
Nonparametric ridge estimation Christopher R. Genovese M. Perone-Pacifico I. Verdinelli Larry A. Wasserman 119 120 0 20 Dec 2012
Learning Manifolds with K-Means and K-Flats Guillermo D. Cañas T. Poggio Lorenzo Rosasco 106 49 0 05 Sep 2012
Manifold estimation and singular deconvolution under Hausdorff loss Christopher R. Genovese M. Perone-Pacifico I. Verdinelli Larry A. Wasserman UQCV 65 101 0 21 Sep 2011
Robust recovery of multiple subspaces by geometric l_p minimization Gilad Lerman Teng Zhang 90 86 0 19 Apr 2011
Minimax Manifold Estimation Christopher R. Genovese M. Perone-Pacifico I. Verdinelli Larry A. Wasserman 84 128 0 04 Jul 2010
Probabilistic Recovery of Multiple Subspaces in Point Clouds by Geometric lp Minimization Gilad Lerman Teng Zhang 95 22 0 09 Feb 2010
K-Dimensional Coding Schemes in Hilbert Spaces Augusto Maurer 96 108 0 03 Feb 2010