Your diffusion model secretly knows the dimension of the data manifold

Your diffusion model secretly knows the dimension of the data manifold

23 December 2022

Georgios Batzolis

Carola-Bibiane Schönlieb

Papers citing "Your diffusion model secretly knows the dimension of the data manifold"

18 / 18 papers shown

Title
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling Xiao Li Zekai Zhang Xiang Li Siyi Chen Zhihui Zhu Peng Wang Qing Qu DiffM 125 1 0 09 Feb 2025
State Combinatorial Generalization In Decision Making With Conditional Diffusion Models Xintong Duan Yutong He Fahim Tajwar Wen-Tse Chen Ruslan Salakhutdinov Jeff Schneider OffRL AI4CE 136 1 0 22 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 Gabriel Loaiza-Ganem 102 8 0 31 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 69 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 68 3 0 02 Oct 2024
Statistical Efficiency of Score Matching: The View from Isoperimetry Frederic Koehler Alexander Heckett Andrej Risteski DiffM 123 51 0 03 Oct 2022
Variational Diffusion Models Diederik P. Kingma Tim Salimans Ben Poole Jonathan Ho DiffM 147 1,111 0 01 Jul 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 163 7,763 0 11 May 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 226 269 0 18 Apr 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 120 657 0 22 Jan 2021
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization Yingfan Wang Haiyang Huang Cynthia Rudin Yaron Shaposhnik 198 312 0 08 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 284 6,401 0 26 Nov 2020
DiffWave: A Versatile Diffusion Model for Audio Synthesis Zhifeng Kong Ming-Yu Liu Jiaji Huang Kexin Zhao Bryan Catanzaro DiffM BDL 99 1,445 0 21 Sep 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 447 17,867 0 19 Jun 2020
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 224 6,875 0 12 Mar 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 404 16,947 0 20 Dec 2013
Testing the Manifold Hypothesis Charles Fefferman S. Mitter Hariharan Narayanan 117 531 0 01 Oct 2013
Intrinsic dimension estimation of data by principal component analysis Mingyu Fan N. Gu Hong Qiao Bo Zhang 89 37 0 10 Feb 2010