AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation | ScienceToStartup | ScienceToStartup

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References (89)

[1]

HGphormer: Heterophilic Graph Transformer

2025Jianshe Wu, Yaolin Liu et al.

[2]

HopGAT: A multi-hop graph attention network with heterophily and degree awareness

2025Hang Zhang, Huan Wang et al.

[3]

GFformer: A Graph Transformer for Extracting All Frequency Information from Large-scale Graphs

Founder's Pitch

"AdvSynGNN enhances graph neural networks' resilience and accuracy in noisy structures through adversarial synthesis and self-corrective propagation."

Graph Neural Networks•Score: 5•View PDF ↗

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AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation

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References (89)

Founder's Pitch

"AdvSynGNN enhances graph neural networks' resilience and accuracy in noisy structures through adversarial synthesis and self-corrective propagation."

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