Knowledge distillation improves graph structure augmentation for graph neural networks
Graph (structure) augmentation aims to perturb the graph structure through heuristic or
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks
L Wu, H Lin, Y Huang, SZ Li - Advances in Neural Information …, 2022 - openreview.net
Graph (structure) augmentation aims to perturb the graph structure through heuristic or
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
Knowledge distillation improves graph structure augmentation for graph neural networks
L Wu, H Lin, Y Huang, SZ Li - … of the 36th International Conference on …, 2022 - dl.acm.org
Graph (structure) augmentation aims to perturb the graph structure through heuristic or
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
[PDF][PDF] Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks
L Wu, H Lin, Y Huang, SZ Li - papers.neurips.cc
Graph (structure) augmentation aims to perturb the graph structure through heuristic or
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
probabilistic rules, enabling the nodes to capture richer contextual information and thus …