{"total":56,"rows":[{"id":"2403.03852","title":"Accelerating Convergence of Score-Based Diffusion Models, Provably","created":"2024-03-06","cited_by_count":76,"area":"diffusion"},{"id":"2408.02320","title":"A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models","created":"2024-08-05","cited_by_count":65,"area":"diffusion"},{"id":"2402.07487","title":"Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial","created":"2024-02-12","cited_by_count":60,"area":"diffusion"},{"id":"2404.09730","title":"Convergence Analysis of Probability Flow ODE for Score-based Generative Models","created":"2024-04-15","cited_by_count":57,"area":"diffusion"},{"id":"2409.18959","title":"O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions","created":"2024-09-27","cited_by_count":50,"area":"diffusion"},{"id":"2410.03601","title":"How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework","created":"2024-10-04","cited_by_count":48,"area":"diffusion"},{"id":"2404.02954","title":"Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections","created":"2024-04-03","cited_by_count":47,"area":"diffusion"},{"id":"2410.18784","title":"Denoising diffusion probabilistic models are optimally adaptive to unknown low dimensionality","created":"2024-10-24","cited_by_count":44,"area":"diffusion"},{"id":"2405.15986","title":"Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity","created":"2024-05-24","cited_by_count":42,"area":"diffusion"},{"id":"2501.12982","title":"Low-dimensional adaptation of diffusion models: Convergence in total variation","created":"2025-01-22","cited_by_count":39,"area":"diffusion"},{"id":"2508.12880","title":"Stochastic Self-Guidance for Training-Free Enhancement of Diffusion Models","created":"2025-08-18","cited_by_count":36,"area":"diffusion"},{"id":"2410.04760","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","created":"2024-10-07","cited_by_count":35,"area":"diffusion"},{"id":"2410.23285","title":"Provable Acceleration for Diffusion Models under Minimal Assumptions","created":"2024-10-30","cited_by_count":27,"area":"diffusion"},{"id":"2404.00551","title":"Convergence of Continuous Normalizing Flows for Learning Probability Distributions","created":"2024-03-31","cited_by_count":26,"area":null},{"id":"2406.12839","title":"Evaluating the design space of diffusion-based generative models","created":"2024-06-18","cited_by_count":26,"area":"diffusion"},{"id":"2504.05300","title":"Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures","created":"2025-04-07","cited_by_count":23,"area":"diffusion"},{"id":"2508.03210","title":"Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance","created":"2025-08-05","cited_by_count":21,"area":"diffusion"},{"id":"2402.13901","title":"Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach","created":"2024-02-21","cited_by_count":19,"area":"diffusion"},{"id":"2502.04849","title":"Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration","created":"2025-02-07","cited_by_count":17,"area":"diffusion"},{"id":"2405.14250","title":"Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors","created":"2024-05-23","cited_by_count":16,"area":"diffusion"},{"id":"2506.24042","title":"Faster Diffusion Models via Higher-Order Approximation","created":"2025-06-30","cited_by_count":16,"area":"diffusion"},{"id":"2510.27562","title":"Optimal Convergence Analysis of DDPM for General Distributions","created":"2025-10-31","cited_by_count":16,"area":"diffusion"},{"id":"2602.01338","title":"High-accuracy sampling for diffusion models and log-concave distributions","created":"2026-02-01","cited_by_count":16,"area":"diffusion"},{"id":"2409.08311","title":"Theoretical guarantees in KL for Diffusion Flow Matching","created":"2024-09-12","cited_by_count":14,"area":"diffusion"},{"id":"2410.14237","title":"Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers","created":"2024-10-18","cited_by_count":14,"area":"diffusion"},{"id":"2410.11275","title":"Shallow diffusion networks provably learn hidden low-dimensional structure","created":"2024-10-15","cited_by_count":12,"area":"diffusion"},{"id":"2412.11251","title":"Wasserstein Bounds for generative diffusion models with Gaussian tail targets","created":"2024-12-15","cited_by_count":10,"area":"diffusion"},{"id":"2506.09681","title":"Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds","created":"2025-06-11","cited_by_count":9,"area":"diffusion"},{"id":"2506.13061","title":"Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2501.18863","title":"Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models","created":"2025-01-31","cited_by_count":8,"area":"diffusion"},{"id":"2508.16306","title":"A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions","created":"2025-08-22","cited_by_count":8,"area":"diffusion"},{"id":"2604.06065","title":"Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities","created":"2026-04-07","cited_by_count":8,"area":"diffusion"},{"id":"2410.13746","title":"Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers","created":"2024-10-17","cited_by_count":7,"area":"diffusion"},{"id":"2510.17608","title":"Non-asymptotic error bounds for probability flow ODEs under weak log-concavity","created":"2025-10-20","cited_by_count":7,"area":"diffusion"},{"id":"2511.04844","title":"Sublinear iterations can suffice even for DDPMs","created":"2025-11-06","cited_by_count":7,"area":"diffusion"},{"id":"2409.00730","title":"Generating Physical Dynamics under Priors","created":"2024-09-01","cited_by_count":6,"area":null},{"id":"2509.02337","title":"Distribution estimation via Flow Matching with Lipschitz guarantees","created":"2025-09-02","cited_by_count":6,"area":"diffusion"},{"id":"2511.07869","title":"Parallel Sampling via Autospeculation","created":"2025-11-11","cited_by_count":6,"area":"diffusion"},{"id":"2512.06702","title":"Pathway to $O(\\sqrt{d})$ Complexity bound under Wasserstein metric of flow-based models","created":"2025-12-07","cited_by_count":4,"area":null},{"id":"2508.08735","title":"Elucidating Rectified Flow with Deterministic Sampler: Polynomial Discretization Complexity for Multi and One-step Models","created":"2025-08-12","cited_by_count":3,"area":"diffusion"},{"id":"2509.03898","title":"Diffusion Generative Models Meet Compressed Sensing, with Applications to Imaging and Finance","created":"2025-09-04","cited_by_count":3,"area":"diffusion"},{"id":"2512.01820","title":"Dimension-free error estimate for diffusion model and optimal scheduling","created":"2025-12-01","cited_by_count":3,"area":"diffusion"},{"id":"2505.01049","title":"Multi-Step Consistency Models: Fast Generation with Theoretical Guarantees","created":"2025-05-02","cited_by_count":2,"area":"diffusion"},{"id":"2604.10857","title":"Query Lower Bounds for Diffusion Sampling","created":"2026-04-12","cited_by_count":2,"area":"diffusion"},{"id":"2508.10944","title":"Non-asymptotic convergence bound of conditional diffusion models","created":"2025-08-13","cited_by_count":1,"area":"diffusion"},{"id":"2603.19670","title":"Load--Reserve Wasserstein Propagation for Isotropic Diffusion Samplers","created":"2026-03-20","cited_by_count":1,"area":"diffusion"},{"id":"2605.21911","title":"Noise Schedule Design for Diffusion Models: An Optimal Control Perspective","created":"2026-05-21","cited_by_count":1,"area":"diffusion"},{"id":"2606.06007","title":"Diffusion Models for Adaptive Sequential Data Generation","created":"2026-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2606.15835","title":"Wasserstein Convergence of ODE-Based Samplers in Decentralized Diffusion Model via Velocity Field Decomposition","created":"2026-06-14","cited_by_count":1,"area":"diffusion"},{"id":"2605.06172","title":"Expressivity of Bi-Lipschitz Normalizing Flows: A Score-Based Diffusion Perspective","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.27769","title":"Smoothed Score Queries and the Complexity of Sampling","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2606.13796","title":"Recursively Trained Diffusion Models: Limiting Collapse Distribution and Spectral Characterization","created":"2026-06-11","cited_by_count":0,"area":"diffusion"},{"id":"2607.06646","title":"Diffusion enabled Optimal Transport distances for graph matching","created":"2026-07-07","cited_by_count":0,"area":null},{"id":"2608.02406","title":"A Unified Kullback--Leibler Divergence Analysis of Generative Diffusion Models via Entropy Production Rate","created":"2026-08-03","cited_by_count":0,"area":"diffusion"},{"id":"2609.29350","title":"Learning a Flow to Self-Supervised Representations","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2610.10190","title":"Universal Local Error and Realized Amplification for the First-Order EDM Predictor","created":"2026-10-07","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}