ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2406.15762
  4. Cited By
Rethinking the Diffusion Models for Numerical Tabular Data Imputation
  from the Perspective of Wasserstein Gradient Flow

Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow

22 June 2024
Zhichao Chen
Haoxuan Li
Fangyikang Wang
Odin Zhang
Hu Xu
Xiaoyu Jiang
Zhihuan Song
Eric H. Wang
    DiffM
ArXiv (abs)PDFHTML

Papers citing "Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow"

2 / 2 papers shown
Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
Fangyikang Wang
Hubery Yin
Shaobin Zhuang
Huminhao Zhu
Yinan Li
Lei Qian
Chao Zhang
Hanbin Zhao
Hui Qian
Chen Li
210
1
0
29 May 2025
Deep Learning for Multivariate Time Series Imputation: A Survey
Deep Learning for Multivariate Time Series Imputation: A SurveyInternational Joint Conference on Artificial Intelligence (IJCAI), 2024
Jun Wang
Wenjie Du
Yiyuan Yang
Linglong Qian
Wei Cao
Yuxuan Liang
Wenjia Wang
Yuxuan Liang
Qingsong Wen
AI4TSSyDaBDL
440
85
0
06 Feb 2024
1