ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation

^*Corresponding author for this work

National University of Defense Technology
School of Information
Key Laboratory of Precision Opto-Mechatronics Technology (Ministry of Education)

Research output: Contribution to journal › Conference article › peer-review

Original language	English
Pages (from-to)	5775-5792
Number of pages	18
Journal	Proceedings of Machine Learning Research
Volume	267
State	Published - 2025
Event	42nd International Conference on Machine Learning, ICML 2025 - Vancouver, Canada Duration: 13 Jul 2025 → 19 Jul 2025

Cite this

@article{f786cc3686b5408eb7ba19cd8da623d3,

title = "ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation",

author = "Tianci Bu and Le Zhou and Wenchuan Yang and Jianhong Mou and Kang Yang and Suoyi Tan and Feng Yao and Jingyuan Wang and Xin Lu",

year = "2025",

language = "英语",

volume = "267",

pages = "5775--5792",

journal = "Proceedings of Machine Learning Research",

issn = "2640-3498",

publisher = "ML Research Press",

note = "42nd International Conference on Machine Learning, ICML 2025 ; Conference date: 13-07-2025 Through 19-07-2025",

}

TY - JOUR

T1 - ProDiff

T2 - 42nd International Conference on Machine Learning, ICML 2025

AU - Bu, Tianci

AU - Zhou, Le

AU - Yang, Wenchuan

AU - Mou, Jianhong

AU - Yang, Kang

AU - Tan, Suoyi

AU - Yao, Feng

AU - Wang, Jingyuan

AU - Lu, Xin

PY - 2025

Y1 - 2025

UR - https://www.scopus.com/pages/publications/105023560242

M3 - 会议文章

AN - SCOPUS:105023560242

SN - 2640-3498

VL - 267

SP - 5775

EP - 5792

JO - Proceedings of Machine Learning Research

JF - Proceedings of Machine Learning Research

Y2 - 13 July 2025 through 19 July 2025

ER -