Project AURIONAI Use-Cases Research & Innovation
graphfamily

TGN (Temporal Graph Networks)

Framework for deep learning on dynamic graphs whose edges arrive as timed events. Paper by Rossi et al. (2020).

Twitter (now X)Twitter (now X)USA
Twitter (now X)
Levelfamily
Classgraph
Parametersnot in the notes
Contextnot in the notes
Released18 Jun 2020
Opennessopen source
Runs onnot in the notes
Statusactive

R&D Topics

Graph neural networks and graph transformersproduced by

Identity

Developer
Twitter (now X)
Family
not in the notes
Released
18 Jun 2020 sourcesannouncement page
Weights published
–
Record checked
12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
GNN Memory modules plus graph operators for continuous-time dynamic graphs
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
graph
Output
graph
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open source
Licence
Apache License 2.0 sources
Access routes
not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
not in the notes
Footprint
Licence is that of the twitter-research/tgn repository (Apache-2.0).
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Lineage

The notes record no lineage for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. arxiv.org/abs/2006.10637 https://arxiv.org/abs/2006.10637
  2. github.com/twitter-research/tgn https://github.com/twitter-research/tgn
  3. GitHub - pyg-team/pytorch_geometric: Graph Neural Network Library for PyTorch github.com https://github.com/pyg-team/pytorch_geometric
  4. pytorch-geometric.readthedocs.io/en/latest/modules/nn.html https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html
  5. huggingface.co/datasets/pwc-archive/methods https://huggingface.co/datasets/pwc-archive/methods
  6. arxiv.org/html/2006.10637 https://arxiv.org/html/2006.10637

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "TGN (Temporal Graph Networks)", https://aurion.semai.id/models/tgn/, records of October 2026.