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APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding
Summary: APAN enables real-time temporal graph embedding with asynchronous propagation attention, decoupling inference from k-hop querying. This yields millisecond-level inference in dense networks with competitive accuracy; code released.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6253
- Venue
- SIGMOD
- Year
- 2021
- Pagerank
- 0.00018846494
- Overall Rank
- 636 | 95.58%
- DOI
-
10.1145/3448016.3457564
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 21 of 21 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 1,387 |
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs |
2022 |
VLDB |
0.00012261568 |
| 3,709 |
Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank |
2023 |
VLDB |
6.8242482e-05 |
| 5,052 |
HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training |
2022 |
SIGMOD |
5.7337977e-05 |
| 5,345 |
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams |
2024 |
VLDB |
5.5567697e-05 |
| 5,443 |
Decoupled Graph Neural Networks for Large Dynamic Graphs |
2023 |
VLDB |
5.5025808e-05 |
| 5,475 |
ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs |
2024 |
VLDB |
5.4869706e-05 |
| 5,710 |
DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training |
2024 |
VLDB |
5.3590055e-05 |
| 6,485 |
EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs |
2023 |
SIGMOD |
5.0453531e-05 |
| 6,985 |
CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression |
2023 |
SIGMOD |
4.8729387e-05 |
| 7,014 |
SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement |
2024 |
SIGMOD |
4.8616315e-05 |
| 7,425 |
Anonymous Edge Representation for Inductive Anomaly Detection in Dynamic Bipartite Graph |
2023 |
VLDB |
4.7328962e-05 |
| 7,749 |
GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs |
2024 |
VLDB |
4.6610143e-05 |
| 8,510 |
Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense |
2024 |
VLDB |
4.4952414e-05 |
| 9,272 |
Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs |
2023 |
VLDB |
4.3652496e-05 |
| 10,035 |
SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,506 |
SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,634 |
PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization |
2025 |
VLDB |
4.1945683e-05 |
| 10,656 |
Effective and Efficient Distributed Temporal Graph Learning through Hotspot Memory Sharing |
2025 |
VLDB |
4.1945683e-05 |
| 10,673 |
When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction |
2025 |
VLDB |
4.1945683e-05 |
| 10,885 |
Efficient Graph Embedding Generation and Update for Large-Scale Temporal Graph |
2025 |
VLDB |
4.1945683e-05 |
| 10,887 |
Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours |
2025 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 10,673 |
When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction |
2025 |
VLDB |
4.1945683e-05 |
| 10,887 |
Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours |
2025 |
VLDB |
4.1945683e-05 |
| 9,272 |
Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs |
2023 |
VLDB |
4.3652496e-05 |
| 2,177 |
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning |
2021 |
VLDB |
9.359876e-05 |
| 6,116 |
GraphAn: Graph-based Subsequence Anomaly Detection |
2020 |
VLDB |
5.2039218e-05 |
| 8,740 |
Historical Embedding-Guided Efficient Large-Scale Federated Graph Learning |
2024 |
SIGMOD |
4.456315e-05 |
| 7,158 |
GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection |
2021 |
SIGMOD |
4.8143783e-05 |
| 4,577 |
Accelerating Dynamic Graph Analytics on GPUs |
2018 |
VLDB |
6.0709631e-05 |
| 5,443 |
Decoupled Graph Neural Networks for Large Dynamic Graphs |
2023 |
VLDB |
5.5025808e-05 |
| 10,936 |
NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention |
2024 |
SIGMOD |
4.1945683e-05 |