Cover Image

Non-asymptotic convergence bound of conditional diffusion models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Li, Mengze
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
by: Bruno, Stefano, et al.
Published: (2023)

Non-asymptotic bounds for forward processes in denoising diffusions: Ornstein-Uhlenbeck is hard to beat
by: Brešar, Miha, et al.
Published: (2024)

Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approach
by: Greco, Giacomo, et al.
Published: (2023)

Inverse design with conditional cascaded diffusion models
by: Habibi, Milad, et al.
Published: (2024)

Critical windows: non-asymptotic theory for feature emergence in diffusion models
by: Li, Marvin, et al.
Published: (2024)

On conditional diffusion models for PDE simulations
by: Shysheya, Aliaksandra, et al.
Published: (2024)

What happens to diffusion model likelihood when your model is conditional?
by: Cross, Mattias, et al.
Published: (2024)

Non-asymptotic error bounds for probability flow ODEs under weak log-concavity
by: Kremling, Gitte, et al.
Published: (2025)

On the global convergence of gradient descent for wide shallow models with bounded nonlinearities
by: Petit, Romain, et al.
Published: (2026)

Probabilistic data quality assessment for structural monitoring data via outlier-resistant conditional diffusion model
by: Li, Qi, et al.
Published: (2026)

Closed-form conditional diffusion models for data assimilation
by: Binder, Brianna, et al.
Published: (2026)

Near Optimal Non-asymptotic Sample Complexity of 1-Identification
by: Li, Zitian, et al.
Published: (2025)

Birth-death dynamics for sampling: Global convergence, approximations and their asymptotics
by: Lu, Yulong, et al.
Published: (2022)

Confidence interval estimation of mixed oil length with conditional diffusion model
by: Yang, Yanfeng, et al.
Published: (2024)

The day-ahead scenario generation method for new energy based on an improved conditional generative diffusion model
by: Wang, Changgang, et al.
Published: (2025)

LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting
by: Li, Te, et al.
Published: (2024)

A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
by: Didi, Kieran, et al.
Published: (2023)

Mallows-type model averaging: Non-asymptotic analysis and all-subset combination
by: Peng, Jingfu
Published: (2025)

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
by: Surendran, Sobihan, et al.
Published: (2024)

Problem-dependent convergence bounds for randomized linear gradient compression
by: Flynn, Thomas, et al.
Published: (2024)

Geological and Well prior assisted full waveform inversion using conditional diffusion models
by: Wang, Fu, et al.
Published: (2024)

Hierarchically branched diffusion models leverage dataset structure for class-conditional generation
by: Tseng, Alex M., et al.
Published: (2022)

Non-asymptotic Convergence of Training Transformers for Next-token Prediction
by: Huang, Ruiquan, et al.
Published: (2024)

Enhancing diffusion models with Gaussianization preprocessing
by: Cunzhi, Li, et al.
Published: (2025)

Sampling from multimodal distributions with warm starts: Non-asymptotic bounds for the Reweighted Annealed Leap-Point Sampler
by: Lee, Holden, et al.
Published: (2025)

Towards SFW sampling for diffusion models via external conditioning
by: Reyes, Camilo Carvajal, et al.
Published: (2025)

Kernel conditional tests from learning-theoretic bounds
by: Massiani, Pierre-François, et al.
Published: (2025)

Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
by: Yu, Zhan, et al.
Published: (2023)

Non-asymptotic spectral bounds on the $\varepsilon$-entropy of kernel classes
by: Takhanov, Rustem
Published: (2022)

On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
by: Chen, Zhiheng, et al.
Published: (2024)

Score dynamics: scaling molecular dynamics with picoseconds timestep via conditional diffusion model
by: Hsu, Tim, et al.
Published: (2023)

Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedure
by: Cai, T. Tony, et al.
Published: (2024)

GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling
by: Vaeth, Philipp, et al.
Published: (2024)

Generative modelling with jump-diffusions
by: Baule, Adrian
Published: (2025)

PRISM-0: A Predicate-Rich Scene Graph Generation Framework for Zero-Shot Open-Vocabulary Tasks
by: Elskhawy, Abdelrahman, et al.
Published: (2025)

A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
by: Hird, Max, et al.
Published: (2026)

Hilbert's projective metric for functions of bounded growth and exponential convergence of Sinkhorn's algorithm
by: Eckstein, Stephan
Published: (2023)

Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities
by: Bordino, Alberto, et al.
Published: (2023)

Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
by: Tian, Ye, et al.
Published: (2023)

Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024)