Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention | Paper Citation Record

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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This paper cites Sys., 2023, vol.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Sys., 2023, vol

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This paper cites A Generalization of Transformer Networks to Graphs.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention A Generalization of Transformer Networks to Graphs

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This paper cites McAuley, Christopher Targett, Qinfeng Shi, and Anton van den Hengel, ”Image-based recommendations on styles and substitutes,” in Proc.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention McAuley, Christopher Targett, Qinfeng Shi, and Anton van den Hengel, ”Image-based recommendations on styles and substitutes,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Rep., 2023, vol

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This paper cites ”Graph representation learning and its applications: A survey,” Sensors, 2023, vol.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention ”Graph representation learning and its applications: A survey,” Sensors, 2023, vol

Reference 13

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention AAAI Conf

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Web Conf., 2021, pp

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This paper cites Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

Reference 16

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This paper cites Borgwardt, ”Structure-aware transformer for graph representation learning,” in Proc.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Borgwardt, ”Structure-aware transformer for graph representation learning,” in Proc

Reference 17

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Jung, ”Learning multi- resolution representations of research patterns in bibliographic networks,” J

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention ICML Work

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Jung, ”Story embedding: Learning distributed representations of stories based on character networks (extended abstract),” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Graph Attention Networks

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Hamilton, Vincent L´etourneau, and Prudencio Tossou, ”Rethinking graph transform- ers with spectral attention,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention ACM SIGKDD Conf

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention AAAI Conf

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Wipf, and Junchi Yan, ”Nodeformer: A scalable graph structure learning transformer for node classification,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Fusion, 2024, vol

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Cyber., 2022, vol

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Woodford, Meng Jiang, and Neil Shah, ”Data augmentation for graph neural networks,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention ACM SIGKDD Conf

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Web Conf., 2022, pp

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention AAAI Conf

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Li, ”Dink-net: Neural clustering on large graphs,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention ”Categorical reparam- eterization with gumbel-softmax,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Maddison, Andriy Mnih, and Yee Whye Teh, ”The concrete distribution: A continuous relaxation of discrete random variables,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Zemel, ”Learning adversarially fair and transferable representa- tions,” in Proc

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Fast Graph Representation Learning with PyTorch Geometric

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

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Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Hamilton, ”Compositional fairness constraints for graph embeddings,” in Proc

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This paper cites an unresolved cited work.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:38:59.532944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5d71ae6-235d-4fda-b759-c441f1968d82 · outbound

This paper cites an unresolved cited work.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:38:59.523238Z

Source-reported events for the cited work

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Observation 1be3bd6b-823f-4121-9564-74ef2bb9900c · outbound

This paper cites Surveys , 2023, vol.

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention Surveys , 2023, vol

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:38:59.511450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers