为了解决这一问题,一种名为去噪扩散桥模型(Denoising Diffusion Bridge Models, DDBMs)的变种应运而生。DDBM 能够建模两个给定分布之间的桥接过程,从而很好地应用于图像翻译、图像修复等任务。然而,这类模型在数学形式上依赖复杂的常微分方程 / 随机微分方程,在生成高分辨率图像时通常需要数百步的迭代,计算效率
[3] Cheng Chi et al. Diffusion policy: Visuomotor policy learning via action diffusion. RSS 2023.[4] Siyuan Zhou et al. Adaptive online replanning with diffusion models. NeurIPS 2024.[5] Jiaming Song et al. Denoising Diffusion Implicit Models, ICLR 2021.
然而,标准扩散模型的设计通常只适用于从随机噪声生成数据的任务,对于图像翻译或图像修复这类明确给定输入和输出之间映射关系的任务并不适合。 为了解决这一问题,一种名为去噪扩散桥模型(Denoising Diffusion Bridge Models, DDBMs)的变种应运而生。DDBM 能够建模两个给定分布之间的桥接过程,从而很好地应用于图像翻译、图...
[1] Long Wei et al. DiffPhyCon: A Generative Approach to Control Complex Physical Systems. NeurIPS 2024. [2] Jonatha Ho et al. Denoising diffusion probabilistic models. NeurIPS 2020. [3] Cheng Chi et al. Diffusion policy: Visuomotor policy learning via action diffusion. RSS 2023. [4] S...
一种名为去噪扩散桥模型(Denoising Diffusion Bridge Models, DDBMs)的变种应运而生。DDBM 能够建模两个给定分布之间的桥接过程,从而很好地应用于图像翻译、图像修复等任务。 论文有两位共同一作。郑凯文为清华大学计算机系三年级博士生,何冠德为德州大学奥斯汀分校(UT Austin)一年级博士生。
Denoising Diffusion Implicit Models. International Conference on Learning Representations.[4] Lu C, Zhou Y, Bao F, et al. DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. Advances in Neural Information Processing Systems.[5] Bansal A, Borgnia E, ...
Diffusion Generative Models(扩散式生成模型)已经在各种生成式建模任务中大放异彩,但是,其复杂的数学推导却常常让大家望而却步,缓慢的生成速度也极大地阻碍了研究的快速迭代和高效部署。研究过 DDPM 的同学可能见到过这种画风的变分法(Variational Inference)推导(截取自 What are Diffusion Models): ...
[3] Cheng Chi et al. Diffusion policy: Visuomotor policy learning via action diffusion. RSS 2023. [4] Siyuan Zhou et al. Adaptive online replanning with diffusion models. NeurIPS 2024. [5] Jiaming Song et al. Denoising Diffusion Implicit Models, ICLR 2021....
Your Denoising Implicit Model is a Sub-optimal Ensemble of Denoising Predictions Thinking fourth dimensionally: Treating Time as a Random Variable in EBMs 3 『在CV、NLP领域的应用』 Novel View Synthesis with Diffusion Models Pyramidal Denoising Di...
@misc{zhang2022gddim, title={gDDIM: Generalized denoising diffusion implicit models}, author={Qinsheng Zhang and Molei Tao and Yongxin Chen}, year={2022}, eprint={2206.05564}, archivePrefix={arXiv}, primaryClass={cs.LG} } Related works ...