Low-dimensional adaptation of diffusion models: Convergence in total variation
Fuente:
arXiv
Guardado en:
| Autores principales: | Liang, Jiadong, Huang, Zhihan, Chen, Yuxin |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Denoising diffusion probabilistic models are optimally adaptive to unknown low dimensionality
por: Huang, Zhihan, et al.
Publicado: (2024)
por: Huang, Zhihan, et al.
Publicado: (2024)
Optimal training-conditional regret for online conformal prediction
por: Liang, Jiadong, et al.
Publicado: (2026)
por: Liang, Jiadong, et al.
Publicado: (2026)
Reflected diffusion models adapt to low-dimensional data
por: Holk, Asbjørn, et al.
Publicado: (2026)
por: Holk, Asbjørn, et al.
Publicado: (2026)
Towards a mathematical theory for consistency training in diffusion models
por: Li, Gen, et al.
Publicado: (2024)
por: Li, Gen, et al.
Publicado: (2024)
Towards a unified framework for guided diffusion models
por: Jiao, Yuchen, et al.
Publicado: (2025)
por: Jiao, Yuchen, et al.
Publicado: (2025)
Blind denoising diffusion models and the blessings of dimensionality
por: Kadkhodaie, Zahra, et al.
Publicado: (2026)
por: Kadkhodaie, Zahra, et al.
Publicado: (2026)
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
por: Horvat, Christian, et al.
Publicado: (2024)
por: Horvat, Christian, et al.
Publicado: (2024)
Semiparametric KSD test: unifying score and distance-based approaches for goodness-of-fit testing
por: Huang, Zhihan, et al.
Publicado: (2025)
por: Huang, Zhihan, et al.
Publicado: (2025)
Hybrid Preference Optimization for Alignment: Provably Faster Convergence Rates by Combining Offline Preferences with Online Exploration
por: Bose, Avinandan, et al.
Publicado: (2024)
por: Bose, Avinandan, et al.
Publicado: (2024)
KL Convergence Guarantees for Score diffusion models under minimal data assumptions
por: Conforti, Giovanni, et al.
Publicado: (2023)
por: Conforti, Giovanni, et al.
Publicado: (2023)
Direct Acquisition Optimization for Low-Budget Active Learning
por: Zhao, Zhuokai, et al.
Publicado: (2024)
por: Zhao, Zhuokai, et al.
Publicado: (2024)
Variance reduction of diffusion model's gradients with Taylor approximation-based control variate
por: Jeha, Paul, et al.
Publicado: (2024)
por: Jeha, Paul, et al.
Publicado: (2024)
Partially factorized variational inference for high-dimensional mixed models
por: Goplerud, Max, et al.
Publicado: (2023)
por: Goplerud, Max, et al.
Publicado: (2023)
Non-asymptotic Convergence of Training Transformers for Next-token Prediction
por: Huang, Ruiquan, et al.
Publicado: (2024)
por: Huang, Ruiquan, et al.
Publicado: (2024)
Improve the Training Efficiency of DRL for Wireless Communication Resource Allocation: The Role of Generative Diffusion Models
por: Zhang, Xinren, et al.
Publicado: (2025)
por: Zhang, Xinren, et al.
Publicado: (2025)
Learning in PINNs: Phase transition, total diffusion, and generalization
por: Anagnostopoulos, Sokratis J., et al.
Publicado: (2024)
por: Anagnostopoulos, Sokratis J., et al.
Publicado: (2024)
Generalization in diffusion models arises from geometry-adaptive harmonic representations
por: Kadkhodaie, Zahra, et al.
Publicado: (2023)
por: Kadkhodaie, Zahra, et al.
Publicado: (2023)
ComS2T: A complementary spatiotemporal learning system for data-adaptive model evolution
por: Zhou, Zhengyang, et al.
Publicado: (2024)
por: Zhou, Zhengyang, et al.
Publicado: (2024)
Asymptotic Time-Uniform Inference for Parameters in Averaged Stochastic Approximation
por: Xie, Chuhan, et al.
Publicado: (2024)
por: Xie, Chuhan, et al.
Publicado: (2024)
Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models
por: Liang, Yuchen, et al.
Publicado: (2025)
por: Liang, Yuchen, et al.
Publicado: (2025)
Frequency-adaptive tensor neural networks for high-dimensional multi-scale problems
por: Huang, Jizu, et al.
Publicado: (2025)
por: Huang, Jizu, et al.
Publicado: (2025)
Estimation and Inference in Distributional Reinforcement Learning
por: Zhang, Liangyu, et al.
Publicado: (2023)
por: Zhang, Liangyu, et al.
Publicado: (2023)
Accelerating Convergence of Score-Based Diffusion Models, Provably
por: Li, Gen, et al.
Publicado: (2024)
por: Li, Gen, et al.
Publicado: (2024)
Optimization and generalization analysis for two-layer physics-informed neural networks without over-parametrization
por: Zeng, Zhihan, et al.
Publicado: (2025)
por: Zeng, Zhihan, et al.
Publicado: (2025)
Connections between reinforcement learning with feedback,test-time scaling, and diffusion guidance: An anthology
por: Jiao, Yuchen, et al.
Publicado: (2025)
por: Jiao, Yuchen, et al.
Publicado: (2025)
Low-dimensional embeddings of high-dimensional data
por: de Bodt, Cyril, et al.
Publicado: (2025)
por: de Bodt, Cyril, et al.
Publicado: (2025)
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
por: Li, Gen, et al.
Publicado: (2023)
por: Li, Gen, et al.
Publicado: (2023)
NDCG-Consistent Softmax Approximation with Accelerated Convergence
por: Pu, Yuanhao, et al.
Publicado: (2025)
por: Pu, Yuanhao, et al.
Publicado: (2025)
Sharp Convergence Rates for Masked Diffusion Models
por: Liang, Yuchen, et al.
Publicado: (2026)
por: Liang, Yuchen, et al.
Publicado: (2026)
GRAG: Graph Retrieval-Augmented Generation
por: Hu, Yuntong, et al.
Publicado: (2024)
por: Hu, Yuntong, et al.
Publicado: (2024)
Information-geometric adaptive sampling for graph diffusion
por: Lu, Yuhui, et al.
Publicado: (2026)
por: Lu, Yuhui, et al.
Publicado: (2026)
Controllable seismic velocity synthesis using generative diffusion models
por: Wang, Fu, et al.
Publicado: (2024)
por: Wang, Fu, et al.
Publicado: (2024)
Infinite-dimensional generative diffusions via Doob's h-transform
por: Pieper-Sethmacher, Thorben, et al.
Publicado: (2026)
por: Pieper-Sethmacher, Thorben, et al.
Publicado: (2026)
When Differential Privacy Meets Wireless Federated Learning: An Improved Analysis for Privacy and Convergence
por: Yaoling, Chen, et al.
Publicado: (2026)
por: Yaoling, Chen, et al.
Publicado: (2026)
Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains
por: Oshima, Hisashi, et al.
Publicado: (2024)
por: Oshima, Hisashi, et al.
Publicado: (2024)
Generative modelling with jump-diffusions
por: Baule, Adrian
Publicado: (2025)
por: Baule, Adrian
Publicado: (2025)
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
por: Abrahamsen, Nilin, et al.
Publicado: (2023)
por: Abrahamsen, Nilin, et al.
Publicado: (2023)
Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
por: Han, Yuze, et al.
Publicado: (2024)
por: Han, Yuze, et al.
Publicado: (2024)
Conditioning non-linear and infinite-dimensional diffusion processes
por: Baker, Elizabeth Louise, et al.
Publicado: (2024)
por: Baker, Elizabeth Louise, et al.
Publicado: (2024)
Consistent support recovery for high-dimensional diffusions
por: Marushkevych, Dmytro, et al.
Publicado: (2025)
por: Marushkevych, Dmytro, et al.
Publicado: (2025)
Ejemplares similares
-
Denoising diffusion probabilistic models are optimally adaptive to unknown low dimensionality
por: Huang, Zhihan, et al.
Publicado: (2024) -
Optimal training-conditional regret for online conformal prediction
por: Liang, Jiadong, et al.
Publicado: (2026) -
Reflected diffusion models adapt to low-dimensional data
por: Holk, Asbjørn, et al.
Publicado: (2026) -
Towards a mathematical theory for consistency training in diffusion models
por: Li, Gen, et al.
Publicado: (2024) -
Towards a unified framework for guided diffusion models
por: Jiao, Yuchen, et al.
Publicado: (2025)