Collaborative-Distilled Diffusion Models (CDDM) for Accelerated and Lightweight Trajectory Prediction
机构 * Department of Civil and Environmental Engineering, University of Washington(华盛顿大学土木与环境工程系)
专题命中 效率与蒸馏 :diffusion(title,abstract)
视觉与机器人
图像生成、文生图、图像编辑、扩散模型和可控生成。
机构 * Department of Civil and Environmental Engineering, University of Washington(华盛顿大学土木与环境工程系)
专题命中 效率与蒸馏 :diffusion(title,abstract)
机构 * Stability AI ; University of Tübingen(图宾根大学)
专题命中 效率与蒸馏 :diffusion(abstract);分类 cs.CV、cs.GR
机构 * Ant Group(蚂蚁集团)
专题命中 效率与蒸馏 :diffusion(abstract);分类 cs.CV
专题命中 效率与蒸馏 :image generation(abstract);分类 cs.CV
机构 * Dept. of Comp. Sci. & Tech.(计算机科学与技术系) ; Institute for AI(人工智能研究院) ; BNRist Center(BNRist中心) ; Tsinghua-Bosch Joint ML Center(清华大学-博世联合机器学习中心) ; THBI Lab(THBI实验室) ; Tsinghua University(清华大学)
专题命中 效率与蒸馏 :image generation(abstract)
Comments @inproceedings{zhang2025sageattention, title={SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration}, author={Zhang, Jintao and Wei, Jia and Zhang, Pengle and Zhu, Jun and Chen, Jianfei}, booktitle={International Conference on Learning Representations (ICLR)}, year={2025} }
Journal ref The Thirteenth International Conference on Learning Representations (ICLR 2025)
专题命中 效率与蒸馏 :diffusion(abstract)
Comments 32 pages