Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs
Summary: Temporal SIR-GN: unsupervised structural NRL that clusters and aggregates neighbor embeddings per timestamp, temporally aggregates those summaries, and iterates up to d hops to encode evolving structural roles. Linear-time in temporal edges, with theoretical guarantees and empirically superior accuracy and scalability on node classification/regression tasks. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Janet Layne (Boise State University)
- 2. Justin Carpenter (Boise State University)
- 3. Edoardo Serra (Boise State University)
- 4. Francesco Gullo (UniCredit)
BibTeX Citation
@article{layne_vldb23,
title = {{Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs}},
author = {Layne, Janet and Carpenter, Justin and Serra, Edoardo and Gullo, Francesco},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {9},
pages = {2075--2089},
doi = {10.14778/3598581.3598583},
url = {https://doi.org/10.14778/3598581.3598583},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,503 | Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense | 2024 | VLDB | 5.4132367e-05 |
| 8,504 | Enabling Window-Based Monotonic Graph Analytics with Reusable Transitional Results for Pattern-Consistent Queries | 2024 | VLDB | 5.4132367e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 920 | APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding | 2021 | SIGMOD | 0.00013209734 |
| 1,123 | Path Problems in Temporal Graphs | 2014 | VLDB | 0.00012089975 |
| 1,409 | TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs | 2022 | VLDB | 0.00010854808 |
| 3,210 | Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank | 2023 | VLDB | 7.6352864e-05 |
| 3,828 | FREDE: Anytime Graph Embeddings | 2021 | VLDB | 7.0903874e-05 |
| 3,896 | Scaling Attributed Network Embedding to Massive Graphs | 2021 | VLDB | 7.0406415e-05 |
| 8,365 | Hunting Temporal Bumps in Graphs with Dynamic Vertex Properties | 2022 | SIGMOD | 5.44244e-05 |
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