Relational models trained on synthetic data for graph databases
In brief
- Graph relational models trained on synthetic data improve performance on real tasks.
- Progressive curriculum learning boosts latent representations without fine-tuning.
- Results outperform approaches relying solely on real data.
A study investigates using graph-based relational models trained on synthetic data to enhance performance on real-world relational classification tasks. Results show that a progressive curriculum learning approach significantly improves latent representations, even without fine-tuning.
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