Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 25, 2026ISPRS International Journal of Geo-InformationOpen Access

DSCFormer: A Dynamic Sparse Causal Attention Network for Efficient Traffic Flow Prediction

View Full Paper
Ask AI
Bookmark
Share

Authors

XFXuhai FanLZLinglong Zhu

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Fan et al. (2026) studied this question.

synapsesocial.com/papers/6ab60fbe406bf401c14687e5https://doi.org/10.3390/ijgi15100437
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Spatio-temporal transformer traffic prediction network based on multi-level causal attention2025 · 4 citations
  2. 2Dynamic Spatial–Temporal Self-Attention Network for Traffic Flow Prediction2024 · 6 citations
  3. 3A Multi-Level Dynamic GCN-Transformer Framework with Spatio-Temporal Interaction for Traffic Flow Prediction2026
  4. 4Traffic Flow Prediction Model Based on Transformer and Dynamic Graph Convolutional Networks2025
  5. 5DSSA-TCN: Exploiting adaptive sparse attention and diffusion graph convolutions in temporal convolutional networks for traffic flow forecasting2025