Cover Image

Optimal Convergence Analysis of DDPM for General Distributions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jiao, Yuchen, Zhou, Yuchen, Li, Gen
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
by: Li, Gen, et al.
Published: (2025)

Towards a unified framework for guided diffusion models
by: Jiao, Yuchen, et al.
Published: (2025)

Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach
by: Jiao, Yuchen, et al.
Published: (2025)

Connections between reinforcement learning with feedback,test-time scaling, and diffusion guidance: An anthology
by: Jiao, Yuchen, et al.
Published: (2025)

Transformers Meet In-Context Learning: A Universal Approximation Theory
by: Li, Gen, et al.
Published: (2025)

Faster Diffusion Models via Higher-Order Approximation
by: Li, Gen, et al.
Published: (2025)

DDPM Score Matching and Distribution Learning
by: Chewi, Sinho, et al.
Published: (2025)

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
by: Li, Gen, et al.
Published: (2023)

Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models
by: Liang, Yuchen, et al.
Published: (2025)

Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
by: Zhou, Yuchen, et al.
Published: (2023)

Minimax Optimality of the Probability Flow ODE for Diffusion Models
by: Cai, Changxiao, et al.
Published: (2025)

When Does Model Collapse Occur in Structured Interactive Learning?
by: Wu, Yuchen, et al.
Published: (2026)

Learning single index model with gradient descent: spectral initialization and precise asymptotics
by: Chen, Yuchen, et al.
Published: (2025)

Instance-dependent Convergence Theory for Diffusion Models
by: Jiao, Yuchen, et al.
Published: (2024)

O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions
by: Li, Gen, et al.
Published: (2024)

Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025)

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
by: Shi, Laixi, et al.
Published: (2023)

Stochastic Optimization in Semi-Discrete Optimal Transport: Convergence Analysis and Minimax Rate
by: Genans, Ferdinand, et al.
Published: (2025)

Minimax-Optimal Multi-Agent Robust Reinforcement Learning
by: Jiao, Yuchen, et al.
Published: (2024)

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)

Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent
by: Patil, Pratik, et al.
Published: (2024)

Convergence of Dirichlet Forms for MCMC Optimal Scaling with Dependent Target Distributions on Large Graphs
by: Ning, Ning
Published: (2022)

Ordinary Least Squares is a Special Case of Transformer
by: Tan, Xiaojun, et al.
Published: (2026)

Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
by: Vardanyan, Elen, et al.
Published: (2023)

Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
by: Li, Gen, et al.
Published: (2023)

Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
by: Li, Gen, et al.
Published: (2025)

Optimal Ridge Regularization for Out-of-Distribution Prediction
by: Patil, Pratik, et al.
Published: (2024)

A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models
by: Li, Gen, et al.
Published: (2024)

A Score-Based Density Formula, with Applications in Diffusion Generative Models
by: Li, Gen, et al.
Published: (2024)

Optimal Bounds for Tyler's M-Estimator for Elliptical Distributions
by: Lau, Lap Chi, et al.
Published: (2025)

Towards a mathematical theory for consistency training in diffusion models
by: Li, Gen, et al.
Published: (2024)

Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
by: Rajaraman, Nived, et al.
Published: (2023)

Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
by: Li, Gen, et al.
Published: (2024)

Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition
by: Lee, Holden, et al.
Published: (2024)

A non-asymptotic distributional theory of approximate message passing for sparse and robust regression
by: Li, Gen, et al.
Published: (2024)

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
by: Li, Gen, et al.
Published: (2020)

Convergence of the Inexact Langevin Algorithm in KL Divergence with Application to Score-based Generative Models
by: Yang, Kaylee Yingxi, et al.
Published: (2022)

Simplicity Bias via Global Convergence of Sharpness Minimization
by: Gatmiry, Khashayar, et al.
Published: (2024)

$L^2$ over Wasserstein: Statistical Analysis for Optimal Transport
by: Passeggeri, Riccardo, et al.
Published: (2026)

Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distribution to Multivariate Settings
by: Ndiaye, Eugene
Published: (2025)