https://github.com/gravins/non-dissipative-propagation-ctdgs
Official reference implementation of our paper "Long Range Propagation on Continuous-Time Dynamic Graphs" accepted at ICML24 and "Effective Non-Dissipative Propagation for Continuous-Time Dynamic Graphs" accepted at Temporal Graph Learning Workshop @ NeurIPS 2023
https://github.com/gravins/non-dissipative-propagation-ctdgs
dynamic-graphs graph-neural-networks graphneuralnetwork ordinary-differential-equations
Last synced: 8 months ago
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Official reference implementation of our paper "Long Range Propagation on Continuous-Time Dynamic Graphs" accepted at ICML24 and "Effective Non-Dissipative Propagation for Continuous-Time Dynamic Graphs" accepted at Temporal Graph Learning Workshop @ NeurIPS 2023
- Host: GitHub
- URL: https://github.com/gravins/non-dissipative-propagation-ctdgs
- Owner: gravins
- License: bsd-3-clause
- Created: 2023-11-22T14:01:28.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-22T18:57:42.000Z (10 months ago)
- Last Synced: 2025-03-28T23:43:28.578Z (8 months ago)
- Topics: dynamic-graphs, graph-neural-networks, graphneuralnetwork, ordinary-differential-equations
- Language: Python
- Homepage:
- Size: 173 MB
- Stars: 7
- Watchers: 3
- Forks: 2
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE