Methods › Graphs › Graph Models › TGN
Temporal Graph Network
TGN
Introduced by Emanuele Rossi et al. in Temporal Graph Networks for Deep Learning on Dynamic Graphs
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Temporal Graph Network, or TGN, is a framework for deep learning on dynamic graphs represented as sequences of timed events. The memory (state) of the model at time t consists of a vector 𝐬ᵢ(t) for each node i the model has seen so far. The memory of a node is updated after an event (e.g. interaction with another node or node-wise change), and its purpose is to represent the node's history in a compressed format. Thanks to this specific module, TGNs have the capability to memorize long term dependencies for each node in the graph. When a new node is encountered, its memory is initialized as the zero vector, and it is then updated for each event involving the node, even after the model has finished training.
Papers archive 2025-07-28
16 shown of 16, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams 24 Jun 2025 · 0 repositories · arXiv:2506.19282
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Trajectory Encoding Temporal Graph Networks 15 Apr 2025 · 1 repository · arXiv:2504.11386
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Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification 6 Nov 2024 · 1 repository · arXiv:2411.03596Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
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Retrofitting Temporal Graph Neural Networks with Transformer 9 Sep 2024 · 1 repository · arXiv:2409.05477
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UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs 17 Jul 2024 · 0 repositories · arXiv:2407.12269
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Temporal Graph Rewiring with Expander Graphs 4 Jun 2024 · 1 repository · arXiv:2406.02362
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Temporal Graph Networks for Graph Anomaly Detection in Financial Networks 27 Mar 2024 · 0 repositories · arXiv:2404.00060
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A Temporal Graph Network Framework for Dynamic Recommendation 24 Mar 2024 · 1 repository · arXiv:2403.16066
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HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers 30 Nov 2023 · 0 repositories · arXiv:2311.18526
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Towards Temporal Edge Regression: A Case Study on Agriculture Trade Between Nations 15 Aug 2023 · 1 repository · arXiv:2308.07883
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Analysis of different temporal graph neural network configurations on dynamic graphs 2 May 2023 · 0 repositories · arXiv:2305.01128
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DyG2Vec: Efficient Representation Learning for Dynamic Graphs 30 Oct 2022 · 2 repositories · arXiv:2210.16906
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Rethinking The Memory Staleness Problem In Dynamics GNN 6 Sep 2022 · 1 repository · arXiv:2209.02462
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Adaptive Data Augmentation on Temporal Graphs 1 Dec 2021 · 0 repositories
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Multi Scale Temporal Graph Networks For Skeleton-based Action Recognition 5 Dec 2020 · 0 repositories · arXiv:2012.02970
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Temporal Graph Networks for Deep Learning on Dynamic Graphs 18 Jun 2020 · 10 repositories · arXiv:2006.10637Syntology ran 4 of 19 samples · 15 unverified
Tasks archive 2025-07-28
20 shown of 27 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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