Corrigendum: Score-based Graph Learning for Urban Flow Prediction

Pengyu Wang; Xiaoman Luo; Wenxin Tai; Kunpeng Zhang; Goce Trajcevsky; Fan Zhou

doi:10.1145/3809159

May 14, 2026ACM Transactions on Intelligent Systems and TechnologyOpen Access

Corrigendum: Score-based Graph Learning for Urban Flow Prediction

View Full Paper

Ask AI

Bookmark

Share

Key Points

This corrigendum addresses errors in the original article on score-based graph learning for urban flow prediction.
Correction of previously published equations and methods in the original article.
Clarification of the graph learning techniques used to analyze urban flow data.
The corrected methods enhance the accuracy of urban flow predictions.
Updated analysis techniques may lead to improved urban planning insights.

Implication

Corrigendum highlights adjustments in graph learning methods for predicting urban flow dynamics.

Abstract

This is a corrigendum for the article "Score-based Graph Learning for Urban Flow Prediction" published in ACM Trans. Intell. Syst. Technol. 15, 3, Article 59 (May 2024), 25 pages.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a095b1b7880e6d24efe0e8b https://doi.org/10.1145/3809159

View Full Paper

Ask AI

Bookmark

Share

Corrigendum: Score-based Graph Learning for Urban Flow Prediction

Key Points

Implication

Abstract

Discussion

Cite This Study

Corrigendum: Score-based Graph Learning for Urban Flow Prediction

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading