[3] Tim Salimans and Jonathan Ho. Progressive distillation for fast sampling of diffusion models. In Proc. ICLR 2022. [4] Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao. Diffsinger: Singing voice synthesis via shallow diffusion mechanism. In Proc. AAAI 2022. [5] https://gith...
Progressive distillation for fast sampling of diffusion models. In Proc. ICLR 2022. [4] Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao. Diffsinger: Singing voice synthesis via shallow diffusion mechanism. In Proc. AAAI 2022. [5] github.com/NATSpeech/NA. A Non-Autoregressive ...
预测速度v,速度是由初始噪声和时间步t直接预测出来的,去噪时通过预测的v和x可以算出当前步的噪声
[3] Tim Salimans and Jonathan Ho. Progressive distillation for fast sampling of diffusion models. In Proc. ICLR 2022. [4] Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao. Diffsinger: Singing voice synthesis via shallow diffusion mechanism. In Proc. AAAI 2022. [5] https://gith...
[3]Tim Salimans and Jonathan Ho. Progressive distillation for fast sampling of diffusion models. In Proc. ICLR 2022. [4]Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao. Diffsinger: Singing voice synthesis via shallow diffusion mechanism. In Proc. AAAI 2022. ...
Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang · Yongxin Chen Paper Project Page 2021-11-17 DEIS accelerates large scale text-to-image eDiff-I and achieves SOTA performance. Update BREAKING CHANGE: v1.0 API changes greatly as we add ρRK-DEIS and...
Diffusion models have recently shown great promise for generative modeling, outperforming GANs on perceptual quality and autoregressive models at density estimation. A remaining downside is their slow sampling time: generating high quality samples takes many hundreds or thousands of model evaluations. Here...
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models Created by Wenliang Zhao*, Lujia Bai*, Yongming Rao, Jie Zhou, Jiwen Lu This code contains the Pytorch implementation for UniPC (NeurIPS 2023). An online demo for UniPC with stable-diffusion. Many thanks for...
【RLChina论文研讨会】第97期 陈华玉 Score Regularized Policy Optimization through Diffusion B 28:56 【RLChina论文研讨会】第97期 胡昊 基于贝叶斯原则的离线到在线强化学习 29:05 【RLChina论文研讨会】第90期 李英儒 Q* meets Thompson Sampling:Scaling up Exploration via Hyp 58:41 【RLChina论文研讨会...
【RLChina论文研讨会】第93期 耿子介 Reinforcement Learning with Tree Search for Fast Macro Pl, 视频播放量 384、弹幕量 0、点赞数 8、投硬币枚数 1、收藏人数 10、转发人数 0, 视频作者 RLChina强化学习社区, 作者简介 ,相关视频:【RLChina论文研讨会】第95期 庄子文