GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks | Paper Citation Record

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This paper cites Aspect-aware graph interaction attention network for aspect category sentiment analysis,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Aspect-aware graph interaction attention network for aspect category sentiment analysis,

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This paper cites Embedding guarantor: Knowledge-enhanced graph learning for new item cold-start recommendation,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Embedding guarantor: Knowledge-enhanced graph learning for new item cold-start recommendation,

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This paper cites Toward adversarially robust recommendation from adaptive fraudster detection,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Toward adversarially robust recommendation from adaptive fraudster detection,

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This paper cites Structure-based protein function prediction using graph convolutional networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Structure-based protein function prediction using graph convolutional networks,

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This paper cites Interpretable chirality-aware graph neural network for quantitative structure activity relationship modeling in drug discovery,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Interpretable chirality-aware graph neural network for quantitative structure activity relationship modeling in drug discovery,

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This paper cites Structure-based robust fractal graph neural network with molecular fingerprint bert for molecular property prediction,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Structure-based robust fractal graph neural network with molecular fingerprint bert for molecular property prediction,

Reference 6

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This paper cites A multi-view graph contrastive learning framework for defending against adversarial attacks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks A multi-view graph contrastive learning framework for defending against adversarial attacks,

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This paper cites Adversarial Attacks on Graph Neural Networks via Meta Learning.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial Attacks on Graph Neural Networks via Meta Learning

Reference 8

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Observation 9b98504b-2d1f-4be1-9c47-53cad887f16b · outbound

This paper cites Exploratory adversarial attacks on graph neural networks for semi- supervised node classification,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Exploratory adversarial attacks on graph neural networks for semi- supervised node classification,

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This paper cites Adversarial attack on graph structured data,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial attack on graph structured data,

Reference 10

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This paper cites Adversarial attacks on graph neural networks via node injections: A hierarchical reinforcement learning approach,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial attacks on graph neural networks via node injections: A hierarchical reinforcement learning approach,

Reference 11

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This paper cites Single-node injection label specificity attack on graph neural networks via reinforcement learning,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Single-node injection label specificity attack on graph neural networks via reinforcement learning,

Reference 12

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This paper cites Tdgia: Effective injection attacks on graph neural networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Tdgia: Effective injection attacks on graph neural networks,

Reference 13

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This paper cites Node injection for class-specific network poisoning,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Node injection for class-specific network poisoning,

Reference 14

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Observation aa2d3132-e259-4b2c-ba8b-2132c928406a · outbound

This paper cites Adversarial attacks on neural networks for graph data,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial attacks on neural networks for graph data,

Reference 15

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This paper cites Adversarial examples for graph data: Deep insights into attack and defense,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial examples for graph data: Deep insights into attack and defense,

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This paper cites All you need is low (rank): Defending against adversarial attacks on graphs,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks All you need is low (rank): Defending against adversarial attacks on graphs,

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This paper cites Robust optimization as data augmentation for large- scale graphs,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Robust optimization as data augmentation for large- scale graphs,

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This paper cites Graph adversarial training: Dynamically regularizing based on graph structure,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Graph adversarial training: Dynamically regularizing based on graph structure,

Reference 19

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This paper cites Robust graph convolutional networks against adversarial attacks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Robust graph convolutional networks against adversarial attacks,

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This paper cites Node similarity preserving graph convolutional networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Node similarity preserving graph convolutional networks,

Reference 21

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This paper cites Robust graph neural networks via unbiased aggregation,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Robust graph neural networks via unbiased aggregation,

Reference 22

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This paper cites Representation learning: A review and new perspectives,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Representation learning: A review and new perspectives,

Reference 23

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This paper cites Disentangled rep- resentation learning,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Disentangled rep- resentation learning,

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This paper cites Disentangled graph convolutional networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Disentangled graph convolutional networks,

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This paper cites Independence promoted graph disentangled networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Independence promoted graph disentangled networks,

Reference 26

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This paper cites Factorizable graph con- volutional networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Factorizable graph con- volutional networks,

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This paper cites Learning disentangled graph convolutional networks locally and globally,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Learning disentangled graph convolutional networks locally and globally,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Disentangled graph contrastive learning with independence promotion,

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This paper cites Hsdn: A high-order structural semantic disentangled neural network,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Hsdn: A high-order structural semantic disentangled neural network,

Reference 30

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This paper cites Debiasing graph neural networks via learning disentangled causal substructure,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Debiasing graph neural networks via learning disentangled causal substructure,

Reference 31

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This paper cites Causal disen- tangled graph neural network for fault diagnosis of complex industrial process,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Causal disen- tangled graph neural network for fault diagnosis of complex industrial process,

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This paper cites The robustness of deep networks: A geometrical perspective,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks The robustness of deep networks: A geometrical perspective,

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This paper cites Understanding deep learning via decision boundary,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Understanding deep learning via decision boundary,

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This paper cites Detecting adversarial examples from sensitivity inconsistency of spatial-transform domain,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Detecting adversarial examples from sensitivity inconsistency of spatial-transform domain,

Reference 35

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This paper cites Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors

Reference 36

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Deep open intent classification with adaptive decision boundary,

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This paper cites Gnnboundary: Towards explaining graph neural networks through the lens of decision boundaries,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Gnnboundary: Towards explaining graph neural networks through the lens of decision boundaries,

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This paper cites Toward robust graph semi-supervised learning against extreme data scarcity,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Toward robust graph semi-supervised learning against extreme data scarcity,

Reference 39

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This paper cites Mutual gnn-mlp distillation for robust graph adversarial defense,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Mutual gnn-mlp distillation for robust graph adversarial defense,

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This paper cites Learning hierarchical spatial-temporal graph representations for robust multivariate industrial anomaly detection,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Learning hierarchical spatial-temporal graph representations for robust multivariate industrial anomaly detection,

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This paper cites Information theoretic learning-enhanced dual-generative adversarial networks with causal representation for robust ood gener- alization,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Information theoretic learning-enhanced dual-generative adversarial networks with causal representation for robust ood gener- alization,

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This paper cites Focusedcleaner: Sanitizing poisoned graphs for robust gnn-based node classification,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Focusedcleaner: Sanitizing poisoned graphs for robust gnn-based node classification,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Graph structure learning for robust graph neural networks,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Graph structure reshaping against adversarial attacks on graph neural networks,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adaptive reliable defense graph for multi-channel robust gcn,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Spectral adversarial training for robust graph neural network,

Reference 47

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This paper cites Cure-gnn: A robust curvature-enhanced graph neural network against adversarial attacks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Cure-gnn: A robust curvature-enhanced graph neural network against adversarial attacks,

Reference 48

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Ergcn: Data enhancement-based robust graph convolutional network against adversarial attacks,

Reference 49

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Empir- ical study of the topology and geometry of deep networks,

Reference 50

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This paper cites Adversarial graph disentanglement with component-specific aggregation,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Adversarial graph disentanglement with component-specific aggregation,

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Semi-Supervised Classification with Graph Convolutional Networks

Reference 52

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GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Graph Attention Networks

Reference 53

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This paper cites Topology attack and defense for graph neural networks: An optimization perspective,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Topology attack and defense for graph neural networks: An optimization perspective,

Reference 54

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This paper cites Robustness of dengue complex network under targeted versus random attack,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Robustness of dengue complex network under targeted versus random attack,

Reference 55

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This paper cites A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,

Reference 56

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This paper cites FuzAG: Fuzzy agglomerative community detection by exploring the notion of self-membership,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks FuzAG: Fuzzy agglomerative community detection by exploring the notion of self-membership,

Reference 57

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This paper cites Cdlib: A Python library to extract, compare and evaluate communities from complex networks,.

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks Cdlib: A Python library to extract, compare and evaluate communities from complex networks,

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