A training strategy that grows GCN depth gradually, using LoRA fine-tuning and identity initialization, is claimed to reduce over-smoothing and improve accuracy of deep vanilla GCNs.
WWW ’19, Association for Computing Machinery, New York, NY, USA (2019)
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Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning
A training strategy that grows GCN depth gradually, using LoRA fine-tuning and identity initialization, is claimed to reduce over-smoothing and improve accuracy of deep vanilla GCNs.