Cover Image

High-accuracy and dimension-free sampling with diffusions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gatmiry, Khashayar, Chen, Sitan, Salim, Adil
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Learning Mixtures of Gaussians Using Diffusion Models
by: Gatmiry, Khashayar, et al.
Published: (2024)

Computing Optimal Regularizers for Online Linear Optimization
by: Gatmiry, Khashayar, et al.
Published: (2024)

On the Role of Depth and Looping for In-Context Learning with Task Diversity
by: Gatmiry, Khashayar, et al.
Published: (2024)

High-accuracy sampling for diffusion models and log-concave distributions
by: Chen, Fan, et al.
Published: (2026)

Gradient dynamics for low-rank fine-tuning beyond kernels
by: Dayi, Arif Kerem, et al.
Published: (2024)

Gaussian random field approximation via Stein's method with applications to wide random neural networks
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)

Efficient Pauli channel estimation with logarithmic quantum memory
by: Chen, Sitan, et al.
Published: (2023)

Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel
by: Gupta, Shivam, et al.
Published: (2024)

Riemannian Proximal Sampler for High-accuracy Sampling on Manifolds
by: Guan, Yunrui, et al.
Published: (2025)

Sublinear iterations can suffice even for DDPMs
by: Zhang, Matthew S., et al.
Published: (2025)

What does guidance do? A fine-grained analysis in a simple setting
by: Chidambaram, Muthu, et al.
Published: (2024)

Adversarial Online Learning with Temporal Feedback Graphs
by: Gatmiry, Khashayar, et al.
Published: (2024)

High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm
by: Srinivasan, Vishwak, et al.
Published: (2024)

High-accuracy log-concave sampling with stochastic queries
by: Chen, Fan, et al.
Published: (2026)

Dimension-free error estimate for diffusion model and optimal scheduling
by: de Bortoli, Valentin, et al.
Published: (2025)

Sparsified-Learning for High-Dimensional Heavy-Tailed Locally Stationary Time Series, Concentration and Oracle Inequalities
by: Wang, Yingjie, et al.
Published: (2025)

A variational approach to dimension-free self-normalized concentration
by: Chugg, Ben, et al.
Published: (2025)

Sampling from multi-modal distributions with polynomial query complexity in fixed dimension via reverse diffusion
by: Vacher, Adrien, et al.
Published: (2024)

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

Score-based sampling without diffusions: Guidance from a simple and modular scheme
by: Wainwright, M. J.
Published: (2025)

Bounds in Wasserstein Distance for Locally Stationary Processes
by: Tinio, Jan Nino G., et al.
Published: (2024)

Bounds in Wasserstein Distance for Locally Stationary Functional Time Series
by: Tinio, Jan Nino G., et al.
Published: (2025)

Distribution-free two-sample testing with blurred total variation distance
by: Hore, Rohan, et al.
Published: (2026)

On consistent estimation of dimension values
by: Cholaquidis, Alejandro, et al.
Published: (2024)

When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
by: Chen, Yuansi, et al.
Published: (2023)

Compressed Empirical Measures (in finite dimensions)
by: Grünewälder, Steffen
Published: (2022)

Consistent support recovery for high-dimensional diffusions
by: Marushkevych, Dmytro, et al.
Published: (2025)

Statistical guarantees for denoising reflected diffusion models
by: Holk, Asbjørn, et al.
Published: (2024)

A distribution-free valid p-value for finite samples of bounded random variables
by: Alvarez, Joaquin
Published: (2024)

Reflected diffusion models adapt to low-dimensional data
by: Holk, Asbjørn, et al.
Published: (2026)

Regularization can make diffusion models more efficient
by: Taheri, Mahsa, et al.
Published: (2025)

The phase diagram of kernel interpolation in large dimensions
by: Zhang, Haobo, et al.
Published: (2024)

Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory
by: Fu, Hengyu, et al.
Published: (2024)

Learning manifold diffusion semigroups from graph transition matrices
by: Cheng, Xiuyuan, et al.
Published: (2026)

On the VC dimension of deep group convolutional neural networks
by: Sepliarskaia, Anna, et al.
Published: (2024)

Bagging Provides Assumption-free Stability
by: Soloff, Jake A., et al.
Published: (2023)

The Limits of Assumption-free Tests for Algorithm Performance
by: Luo, Yuetian, et al.
Published: (2024)

Distribution free M-estimation
by: Areces, Felipe, et al.
Published: (2025)

KL Convergence Guarantees for Score diffusion models under minimal data assumptions
by: Conforti, Giovanni, et al.
Published: (2023)