Verifying the Union of Manifolds Hypothesis for Image Data

6 July 2022

Papers citing "Verifying the Union of Manifolds Hypothesis for Image Data"

36 / 36 papers shown

Title
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning Francesco Diana André Nusser Chuan Xu Giovanni Neglia 27 0 0 15 May 2025
Optimal Stochastic Trace Estimation in Generative Modeling Xinyang Liu Hengrong Du Wei Deng Ruqi Zhang AI4TS 52 0 0 26 Feb 2025
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals Nico Pelleriti Max Zimmer Elias Wirth Sebastian Pokutta 44 0 0 24 Feb 2025
Beyond Fixed Horizons: A Theoretical Framework for Adaptive Denoising Diffusions Soren Christensen C. Strauch Lukas Trottner DiffM 103 0 0 31 Jan 2025
Towards Scalable Topological Regularizers Hiu-Tung Wong Darrick Lee Hong Yan BDL 59 0 0 24 Jan 2025
Understanding How Nonlinear Layers Create Linearly Separable Features for Low-Dimensional Data Alec S. Xu Can Yaras Peng Wang Q. Qu 30 0 0 04 Jan 2025
A Geometric Framework for Understanding Memorization in Generative Models Brendan Leigh Ross Hamidreza Kamkari Tongzi Wu Rasa Hosseinzadeh Zhaoyan Liu George Stein Jesse C. Cresswell G. Loaiza-Ganem 61 6 0 31 Oct 2024
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax I. Butakov Alexander Sememenko Alexander Tolmachev Andrey Gladkov Marina Munkhoeva Alexey Frolov 37 0 0 09 Oct 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds Hong Ye Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 57 0 0 13 Aug 2024
Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction Benjamin Matthias Ruppik Michael Heck Carel van Niekerk Renato Vukovic Hsien-chin Lin Shutong Feng Marcus Zibrowius Milica Gašić 45 2 0 07 Aug 2024
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation Amartya Sanyal Yaxi Hu Yaodong Yu Yian Ma Yixin Wang Bernhard Schölkopf OODD 48 1 0 27 Jun 2024
A Wiener process perspective on local intrinsic dimension estimation methods Piotr Tempczyk Łukasz Garncarek Dominik Filipiak Adam Kurpisz 44 1 0 24 Jun 2024
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models Hamidreza Kamkari Brendan Leigh Ross Rasa Hosseinzadeh Jesse C. Cresswell G. Loaiza-Ganem DiffM 40 11 0 05 Jun 2024
Guiding a Diffusion Model with a Bad Version of Itself Tero Karras M. Aittala Tuomas Kynkaanniemi J. Lehtinen Timo Aila S. Laine 28 58 0 04 Jun 2024
Hardness of Learning Neural Networks under the Manifold Hypothesis B. Kiani Jason Wang Melanie Weber 45 3 0 03 Jun 2024
A theory of stratification learning Eddie Aamari Clément Berenfeld 37 0 0 30 May 2024
Training-free Editioning of Text-to-Image Models Jinqi Wang Yunfei Fu Zhangcan Ding Bailin Deng Yu-Kun Lai Yipeng Qin DiffM VLM 42 0 0 27 May 2024
Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates Connor Mooney Zhongjian Wang Jack Xin Yifeng Yu 45 2 0 25 May 2024
Deep Regression Representation Learning with Topology Shihao Zhang Kenji Kawaguchi Angela Yao 30 1 0 22 Apr 2024
A Geometric Explanation of the Likelihood OOD Detection Paradox Hamidreza Kamkari Brendan Leigh Ross Jesse C. Cresswell Anthony L. Caterini Rahul G. Krishnan G. Loaiza-Ganem OODD 34 9 0 27 Mar 2024
Data-induced multiscale losses and efficient multirate gradient descent schemes Juncai He Liangchen Liu Yen-Hsi Tsai 27 0 0 05 Feb 2024
Mapping the Multiverse of Latent Representations Jeremy Wayland Corinna Coupette Bastian Alexander Rieck 56 7 0 02 Feb 2024
Plug-and-Play image restoration with Stochastic deNOising REgularization Marien Renaud Jean Prost Arthur Leclaire Nicolas Papadakis DiffM 52 7 0 01 Feb 2024
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images N. Konz Maciej Mazurowski 25 5 0 16 Jan 2024
Deep Generative Models for Detector Signature Simulation: A Taxonomic Review Baran Hashemi Claudius Krause 30 16 0 15 Dec 2023
Latent SDEs on Homogeneous Spaces Sebastian Zeng Florian Graf Roland Kwitt BDL 35 7 0 28 Jun 2023
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models Ba-Hien Tran Giulio Franzese Pietro Michiardi Maurizio Filippone DiffM 28 3 0 30 May 2023
Unpaired Downscaling of Fluid Flows with Diffusion Bridges Tobias Bischoff Katherine Deck 29 14 0 02 May 2023
Topological Singularity Detection at Multiple Scales Julius von Rohrscheidt Bastian Alexander Rieck 48 9 0 30 Sep 2022
Neural Implicit Manifold Learning for Topology-Aware Density Estimation Brendan Leigh Ross G. Loaiza-Ganem Anthony L. Caterini Jesse C. Cresswell AI4CE 33 2 0 22 Jun 2022
Conditional Injective Flows for Bayesian Imaging AmirEhsan Khorashadizadeh K. Kothari Leonardo Salsi Ali Aghababaei Harandi Maarten V. de Hoop Ivan Dokmanić MedIm 26 16 0 15 Apr 2022
Riemannian Score-Based Generative Modelling Valentin De Bortoli Emile Mathieu M. Hutchinson James Thornton Yee Whye Teh Arnaud Doucet DiffM 222 165 0 06 Feb 2022
Tangent Space and Dimension Estimation with the Wasserstein Distance Uzu Lim Harald Oberhauser Vidit Nanda 44 8 0 12 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 176 1,111 0 27 Apr 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 197 261 0 18 Apr 2021
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,217 0 01 Sep 2014