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Statistical Efficiency of Score Matching: The View from Isoperimetry

Statistical Efficiency of Score Matching: The View from Isoperimetry

3 October 2022
Frederic Koehler
Alexander Heckett
Andrej Risteski
    DiffM
ArXivPDFHTML

Papers citing "Statistical Efficiency of Score Matching: The View from Isoperimetry"

37 / 37 papers shown
Title
Proper scoring rules for estimation and forecast evaluation
Proper scoring rules for estimation and forecast evaluation
Kartik Waghmare
Johanna Ziegel
AI4TS
33
0
0
02 Apr 2025
On the Generalization Properties of Diffusion Models
On the Generalization Properties of Diffusion Models
Puheng Li
Zhong Li
Huishuai Zhang
Jiang Bian
64
29
0
13 Mar 2025
Discrete distributions are learnable from metastable samples
Discrete distributions are learnable from metastable samples
Abhijith Jayakumar
A. Lokhov
Sidhant Misra
Marc Vuffray
37
1
0
17 Oct 2024
Shallow diffusion networks provably learn hidden low-dimensional
  structure
Shallow diffusion networks provably learn hidden low-dimensional structure
Nicholas M. Boffi
Arthur Jacot
Stephen Tu
Ingvar M. Ziemann
DiffM
29
1
0
15 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
Promises and Pitfalls of Generative Masked Language Modeling:
  Theoretical Framework and Practical Guidelines
Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines
Yuchen Li
Alexandre Kirchmeyer
Aashay Mehta
Yilong Qin
Boris Dadachev
Kishore Papineni
Sanjiv Kumar
Andrej Risteski
38
0
0
22 Jul 2024
Hierarchic Flows to Estimate and Sample High-dimensional Probabilities
Hierarchic Flows to Estimate and Sample High-dimensional Probabilities
Etienne Lempereur
Stéphane Mallat
37
1
0
06 May 2024
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models
Jingyang Zhang
Jingwei Sun
Eric C. Yeats
Ouyang Yang
Martin Kuo
Jianyi Zhang
Hao Frank Yang
Hai Li
32
41
0
03 Apr 2024
Provably Robust Score-Based Diffusion Posterior Sampling for
  Plug-and-Play Image Reconstruction
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
Xingyu Xu
Yuejie Chi
DiffM
34
20
0
25 Mar 2024
Score-based Diffusion Models via Stochastic Differential Equations -- a
  Technical Tutorial
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
Wenpin Tang
Hanyang Zhao
DiffM
36
23
0
12 Feb 2024
Contractive Diffusion Probabilistic Models
Contractive Diffusion Probabilistic Models
Wenpin Tang
Hanyang Zhao
DiffM
36
12
0
23 Jan 2024
Reflected Schrödinger Bridge for Constrained Generative Modeling
Reflected Schrödinger Bridge for Constrained Generative Modeling
Wei Deng
Yu Chen
Nicole Tianjiao Yang
Hengrong Du
Qi Feng
Ricky T. Q. Chen
21
7
0
06 Jan 2024
Adversarial Estimation of Topological Dimension with Harmonic Score Maps
Adversarial Estimation of Topological Dimension with Harmonic Score Maps
Eric C. Yeats
Cameron Darwin
Frank Liu
Hai Li
26
2
0
11 Dec 2023
Improved Sample Complexity Bounds for Diffusion Model Training
Improved Sample Complexity Bounds for Diffusion Model Training
Shivam Gupta
Aditya Parulekar
Eric Price
Zhiyang Xun
17
2
0
23 Nov 2023
A Unified Approach to Learning Ising Models: Beyond Independence and
  Bounded Width
A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width
Jason Gaitonde
Elchanan Mossel
12
8
0
15 Nov 2023
Sample Complexity Bounds for Score-Matching: Causal Discovery and
  Generative Modeling
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling
Zhenyu Zhu
Francesco Locatello
V. Cevher
11
6
0
27 Oct 2023
Particle-based Variational Inference with Generalized Wasserstein
  Gradient Flow
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow
Ziheng Cheng
Shiyue Zhang
Longlin Yu
Cheng Zhang
BDL
24
6
0
25 Oct 2023
Closed-Form Diffusion Models
Closed-Form Diffusion Models
Christopher Scarvelis
Haitz Sáez de Ocáriz Borde
Justin Solomon
DiffM
90
9
0
19 Oct 2023
Sampling Multimodal Distributions with the Vanilla Score: Benefits of
  Data-Based Initialization
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler
T. Vuong
DiffM
SyDa
11
3
0
03 Oct 2023
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3)
  for Visual Robotic Manipulation
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation
Hyunwoo Ryu
Jiwoo Kim
Hyun Seok Ahn
Junwoo Chang
Joohwan Seo
Taehan Kim
Yubin Kim
Chaewon Hwang
Jongeun Choi
R. Horowitz
DiffM
19
33
0
06 Sep 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive
  Noise Models
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Tianyu Chen
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
CML
22
1
0
30 Jun 2023
Fit Like You Sample: Sample-Efficient Generalized Score Matching from
  Fast Mixing Diffusions
Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions
Yilong Qin
Andrej Risteski
DiffM
19
2
0
15 Jun 2023
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative
  Models
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li
Yuting Wei
Yuxin Chen
Yuejie Chi
DiffM
29
57
0
15 Jun 2023
Provable benefits of score matching
Provable benefits of score matching
Chirag Pabbaraju
Dhruv Rohatgi
A. Sevekari
Holden Lee
Ankur Moitra
Andrej Risteski
11
9
0
03 Jun 2023
White-Box Transformers via Sparse Rate Reduction
White-Box Transformers via Sparse Rate Reduction
Yaodong Yu
Sam Buchanan
Druv Pai
Tianzhe Chu
Ziyang Wu
Shengbang Tong
B. Haeffele
Y. Ma
ViT
16
80
0
01 Jun 2023
Conditionally Strongly Log-Concave Generative Models
Conditionally Strongly Log-Concave Generative Models
Florentin Guth
Etienne Lempereur
Joan Bruna
S. Mallat
27
3
0
31 May 2023
Stein $Π$-Importance Sampling
Stein ΠΠΠ-Importance Sampling
Congye Wang
Ye Chen
Heishiro Kanagawa
Chris J. Oates
29
2
0
17 May 2023
Provably Convergent Schrödinger Bridge with Applications to
  Probabilistic Time Series Imputation
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
Yu Chen
Wei Deng
Shikai Fang
Fengpei Li
Ni Yang
Yikai Zhang
Kashif Rasul
Shandian Zhe
Anderson Schneider
Yuriy Nevmyvaka
OT
AI4TS
20
25
0
12 May 2023
Solving Inverse Problems with Score-Based Generative Priors learned from
  Noisy Data
Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data
Asad Aali
Marius Arvinte
Sidharth Kumar
Jonathan I. Tamir
DiffM
MedIm
32
26
0
02 May 2023
Reflected Diffusion Models
Reflected Diffusion Models
Aaron Lou
Stefano Ermon
22
49
0
10 Apr 2023
Your diffusion model secretly knows the dimension of the data manifold
Your diffusion model secretly knows the dimension of the data manifold
Jan Stanczuk
Georgios Batzolis
Teo Deveney
Carola-Bibiane Schönlieb
DiffM
24
24
0
23 Dec 2022
Improved Analysis of Score-based Generative Modeling: User-Friendly
  Bounds under Minimal Smoothness Assumptions
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions
Hongrui Chen
Holden Lee
Jianfeng Lu
DiffM
11
124
0
03 Nov 2022
Convergence of the Inexact Langevin Algorithm and Score-based Generative
  Models in KL Divergence
Convergence of the Inexact Langevin Algorithm and Score-based Generative Models in KL Divergence
Kaylee Yingxi Yang
Andre Wibisono
16
12
0
02 Nov 2022
Convergence of score-based generative modeling for general data
  distributions
Convergence of score-based generative modeling for general data distributions
Holden Lee
Jianfeng Lu
Yixin Tan
DiffM
177
128
0
26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models
  with minimal data assumptions
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen
Sinho Chewi
Jungshian Li
Yuanzhi Li
Adil Salim
Anru R. Zhang
DiffM
123
245
0
22 Sep 2022
Fast approximations of the Jeffreys divergence between univariate
  Gaussian mixture models via exponential polynomial densities
Fast approximations of the Jeffreys divergence between univariate Gaussian mixture models via exponential polynomial densities
Frank Nielsen
22
12
0
13 Jul 2021
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