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GitHub / navid-naderi / LinkSchedulingGNNs_SupervisionStudy
A comparative study of different supervision levels (supervised/unsupervised/self-supervised) when training graph neural network models for link scheduling in wireless networks.
Stars: 4
Forks: 4
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 135 KB
Dependencies:
0
Created: over 2 years ago
Updated: over 1 year ago
Last pushed: over 2 years ago
Last synced: about 1 year ago
Topics: contrastive-learning, graph-neural-networks, graph-representation-learning, interference-mitigation, link-schuedling, power-control, self-supervised-learning, supervised-learning, supervision, unsupervised-learning, wireless-communications
Files
No dependencies found