arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

New York University(纽约大学)

2026-06-10 至 2026-06-10 共收录 3
2602.09639 2026-06-10 cs.LG stat.ML 版本更新

Blind denoising diffusion models and the blessings of dimensionality

盲去噪扩散模型与维度的祝福

Zahra Kadkhodaie, Aram-Alexandre Pooladian, Sinho Chewi, Eero Simoncelli

机构 * Flatiron Institute, Simons Foundation(Flatiron研究院,Simons基金会) Foundations of Data Science, Yale University(数据科学基础,耶鲁大学) Department of Statistics and Data Science, Yale University(统计与数据科学系,耶鲁大学) Ctr. for Neural Science & Courant Institute, New York University(神经科学中心及Courant学院,纽约大学)

AI总结 提出盲去噪扩散模型(BDDM),通过不向神经网络传递噪声幅度来简化设计,并在数据内在维度低于环境维度的假设下证明其正确性,实验显示自适应方案的优势。

Comments 39 pages, 13 figures; Accepted to ICML 2025 FoGen workshop

详情

展开后加载摘要…

URL PDF HTML 收藏
2507.22017 2026-06-10 eess.IV cs.CV 版本更新

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm

Cyst-X:用于胰腺囊性肿瘤恶性风险分层的多中心MRI基准与联邦学习框架

Hongyi Pan, Gorkem Durak, Elif Keles, Ziliang Hong, Deniz Seyithanoglu, Zheyuan Zhang, Alpay Medetalibeyoglu, Halil Ertugrul Aktas, Andrea Mia Bejar, Yavuz Taktak, Gulbiz Dagoglu Kartal, Mehmet Sukru Erturk, Timurhan Cebeci, Yury Velichko, Lili Zhao, Emil Agarunov, Federica Proietto Salanitri, Concetto Spampinato, Pallavi Tiwari, Ziyue Xu, Sachin Jambawalikar, Ivo G. Schoots, Marco J. Bruno, Chenchan Huang, Candice W. Bolan, Tamas Gonda, Frank H. Miller, Rajesh N. Keswani, Michael B. Wallace, Ulas Bagci

机构 * Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University(机器与混合智能实验室,放射科,西北大学) Istanbul Faculty of Medicine, Istanbul University(伊斯坦布尔大学医学学院) Department of Biomedical Engineering and Radiology, University of Wisconsin-Madison(生物医学工程与放射科,威斯康星大学麦迪逊分校) Department of Preventive Medicine, Northwestern University(预防医学系,西北大学) Division of Gastroenterology and Hepatology, New York University(消化内科与肝病科,纽约大学) Department of Electrical, Electronic and Computer Engineering, University of Catania(电气、电子和计算机工程系,卡塔尼亚大学) NVIDIA Department of Radiology, Columbia University(放射科,哥伦比亚大学) Department of Radiology and Nuclear Medicine, Erasmus Medical Center(放射科与核医学科,埃因霍温医学院) Department of Gastroenterology and Hepatology, Erasmus Medical Center(消化内科与肝病科,埃因霍温医学院) Department of Radiology, New York University(放射科,纽约大学) Division of Gastroenterology and Hepatology, Mayo Clinic Florida(消化内科与肝病科,迈阿密诊所佛罗里达分部) Department of Gastroenterology and Hepatology, Northwestern University(消化内科与肝病科,西北大学)

AI总结 提出Cyst-X,一个多中心MRI基准和联邦学习框架,用于IPMN恶性风险分层,结合PanSegNet分割器和3D DenseNet-121分类器,在内部交叉验证中达到0.85的AUC,性能与放射科医生相当。

详情

展开后加载摘要…

URL PDF HTML 收藏
2506.14753 2026-06-10 cs.CV cs.LG 版本更新

Cost-Aware Routing for Efficient Text-To-Image Generation

面向文本到图像生成的高效路由:成本感知方法

Qinchan Li, Kenneth Chen, Changyue Su, Wittawat Jitkrittum, Qi Sun, Patsorn Sangkloy

机构 * Tandon School of Engineering, New York University(纽约大学Tandon工程学院) Google(谷歌) Eigen 4D Inc.(Eigen 4D公司)

AI总结 提出成本感知路由框架,根据提示复杂度自动选择不同去噪步数或模型,在保证高质量的同时降低计算成本,优于单一模型。

Comments Accepted by TMLR

详情

展开后加载摘要…

URL PDF HTML 收藏