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Generalization in diffusion models arises from geometry-adaptive
  harmonic representations

Generalization in diffusion models arises from geometry-adaptive harmonic representations

4 October 2023
Zahra Kadkhodaie
Florentin Guth
Eero P. Simoncelli
Stéphane Mallat
    AI4CE
    DiffM
ArXivPDFHTML

Papers citing "Generalization in diffusion models arises from geometry-adaptive harmonic representations"

16 / 16 papers shown
Title
Generalization through variance: how noise shapes inductive biases in diffusion models
Generalization through variance: how noise shapes inductive biases in diffusion models
John J. Vastola
DiffM
95
1
0
16 Apr 2025
On Memorization in Diffusion Models
On Memorization in Diffusion Models
Xiangming Gu
Chao Du
Tianyu Pang
Chongxuan Li
Min-Bin Lin
Ye Wang
DiffM
TDI
166
43
0
21 Feb 2025
Density Ratio Estimation with Conditional Probability Paths
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu
Arto Klami
Aapo Hyvarinen
Anna Korba
Omar Chehab
62
0
0
04 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Daniela de Albuquerque
John Pearson
DiffM
51
0
0
03 Jan 2025
A Geometric Framework for Understanding Memorization in Generative Models
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
40
6
0
31 Oct 2024
Influence Functions for Scalable Data Attribution in Diffusion Models
Influence Functions for Scalable Data Attribution in Diffusion Models
Bruno Mlodozeniec
Runa Eschenhagen
Juhan Bae
Alexander Immer
David Krueger
Richard E. Turner
TDI
DiffM
75
4
0
17 Oct 2024
On Diffusion Models for Multi-Agent Partial Observability: Shared Attractors, Error Bounds, and Composite Flow
On Diffusion Models for Multi-Agent Partial Observability: Shared Attractors, Error Bounds, and Composite Flow
Tonghan Wang
Heng Dong
Yanchen Jiang
David C. Parkes
Milind Tambe
DiffM
39
2
0
17 Oct 2024
On the Relation Between Linear Diffusion and Power Iteration
On the Relation Between Linear Diffusion and Power Iteration
Dana Weitzner
M. Delbracio
P. Milanfar
Raja Giryes
DiffM
29
0
0
16 Oct 2024
Linear Convergence of Diffusion Models Under the Manifold Hypothesis
Linear Convergence of Diffusion Models Under the Manifold Hypothesis
Peter Potaptchik
Iskander Azangulov
George Deligiannidis
DiffM
33
5
0
11 Oct 2024
Classification-Denoising Networks
Classification-Denoising Networks
Louis Thiry
Florentin Guth
29
0
0
04 Oct 2024
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion
  Models
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models
Gen Li
Yuting Wei
Yuejie Chi
Yuxin Chen
DiffM
33
21
0
05 Aug 2024
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone
  Generation
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation
Guillaume Huguet
James Vuckovic
Kilian Fatras
Eric Thibodeau-Laufer
Pablo Lemos
...
Jarrid Rector-Brooks
Tara Akhound-Sadegh
Michael M. Bronstein
Alexander Tong
A. Bose
32
26
0
30 May 2024
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Mian Zou
Baosheng Yu
Yibing Zhan
Siwei Lyu
Kede Ma
CVBM
45
2
0
14 May 2024
Dynamical Regimes of Diffusion Models
Dynamical Regimes of Diffusion Models
Giulio Biroli
Tony Bonnaire
Valentin De Bortoli
Marc Mézard
DiffM
50
40
0
28 Feb 2024
Closed-Form Diffusion Models
Closed-Form Diffusion Models
Christopher Scarvelis
Haitz Sáez de Ocáriz Borde
Justin Solomon
DiffM
90
9
0
19 Oct 2023
Learning multi-scale local conditional probability models of images
Learning multi-scale local conditional probability models of images
Zahra Kadkhodaie
Florentin Guth
S. Mallat
Eero P. Simoncelli
DiffM
37
17
0
06 Mar 2023
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