{"total":87,"rows":[{"id":"2103.00111","title":"Graph Self-Supervised Learning: A Survey","created":"2021-02-27","cited_by_count":289,"area":null},{"id":"2106.05819","title":"Adversarial Graph Augmentation to Improve Graph Contrastive Learning","created":"2021-06-10","cited_by_count":200,"area":null},{"id":"2102.10757","title":"Self-Supervised Learning of Graph Neural Networks: A Unified Review","created":"2021-02-22","cited_by_count":184,"area":null},{"id":"2105.07342","title":"Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive","created":"2021-05-16","cited_by_count":136,"area":null},{"id":"2202.08235","title":"Data Augmentation for Deep Graph Learning: A Survey","created":"2022-02-16","cited_by_count":133,"area":null},{"id":"2112.02472","title":"Augmentation-Free Self-Supervised Learning on Graphs","created":"2021-12-05","cited_by_count":94,"area":null},{"id":"2304.05055","title":"A Comprehensive Survey on Deep Graph Representation Learning","created":"2023-04-11","cited_by_count":72,"area":null},{"id":"2206.01535","title":"Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination","created":"2022-06-03","cited_by_count":69,"area":null},{"id":"2108.09896","title":"Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection","created":"2021-08-23","cited_by_count":67,"area":null},{"id":"2202.08871","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","created":"2022-02-17","cited_by_count":62,"area":null},{"id":"2201.03662","title":"Learning Fair Node Representations with Graph Counterfactual Fairness","created":"2022-01-10","cited_by_count":58,"area":null},{"id":"2108.06479","title":"Contrastive Self-supervised Sequential Recommendation with Robust Augmentation","created":"2021-08-14","cited_by_count":56,"area":null},{"id":"2212.00535","title":"Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View","created":"2022-12-01","cited_by_count":55,"area":null},{"id":"2210.08443","title":"CLEAR: Generative Counterfactual Explanations on Graphs","created":"2022-10-16","cited_by_count":48,"area":null},{"id":"2306.06063","title":"Virtual Node Tuning for Few-shot Node Classification","created":"2023-06-09","cited_by_count":46,"area":null},{"id":"2105.00522","title":"Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer","created":"2021-05-02","cited_by_count":45,"area":null},{"id":"2405.09591","title":"A Comprehensive Survey on Data Augmentation","created":"2024-05-15","cited_by_count":40,"area":null},{"id":"2210.00643","title":"Spectral Augmentation for Self-Supervised Learning on Graphs","created":"2022-10-02","cited_by_count":39,"area":null},{"id":"2106.09645","title":"Prototypical Graph Contrastive Learning","created":"2021-06-17","cited_by_count":37,"area":null},{"id":"2307.07107","title":"Graph Positional and Structural Encoder","created":"2023-07-14","cited_by_count":33,"area":null},{"id":"2405.11868","title":"Towards Graph Contrastive Learning: A Survey and Beyond","created":"2024-05-20","cited_by_count":26,"area":null},{"id":"2110.02591","title":"Weakly-supervised Text Classification Based on Keyword Graph","created":"2021-10-06","cited_by_count":25,"area":null},{"id":"2301.12458","title":"SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking","created":"2023-01-29","cited_by_count":23,"area":null},{"id":"2202.08333","title":"Self-Supervised Representation Learning via Latent Graph Prediction","created":"2022-02-16","cited_by_count":22,"area":null},{"id":"2209.00065","title":"ViA: View-invariant Skeleton Action Representation Learning via Motion Retargeting","created":"2022-08-31","cited_by_count":22,"area":null},{"id":"2210.08345","title":"Augmentation-Free Graph Contrastive Learning of Invariant-Discriminative Representations","created":"2022-10-15","cited_by_count":21,"area":null},{"id":"2410.10365","title":"SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples","created":"2024-10-14","cited_by_count":20,"area":null},{"id":"2108.10733","title":"Graph Neural Networks: Methods, Applications, and Opportunities","created":"2021-08-24","cited_by_count":16,"area":null},{"id":"2111.10698","title":"Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming","created":"2021-11-20","cited_by_count":15,"area":null},{"id":"2209.06560","title":"Graph Contrastive Learning with Personalized Augmentation","created":"2022-09-14","cited_by_count":14,"area":null},{"id":"2210.08792","title":"Unifying Graph Contrastive Learning with Flexible Contextual Scopes","created":"2022-10-17","cited_by_count":14,"area":null},{"id":"2204.13846","title":"RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning","created":"2022-04-29","cited_by_count":12,"area":null},{"id":"2305.06437","title":"Self-Supervised Video Representation Learning via Latent Time Navigation","created":"2023-05-10","cited_by_count":11,"area":null},{"id":"2306.15154","title":"Contrastive Meta-Learning for Few-shot Node Classification","created":"2023-06-27","cited_by_count":11,"area":null},{"id":"2212.09970","title":"Data Augmentation on Graphs: A Technical Survey","created":"2022-12-20","cited_by_count":10,"area":null},{"id":"2110.07336","title":"RPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-Training","created":"2021-10-08","cited_by_count":9,"area":null},{"id":"2203.15936","title":"Supervised Graph Contrastive Learning for Few-shot Node Classification","created":"2022-03-29","cited_by_count":9,"area":null},{"id":"2403.15520","title":"GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation","created":"2024-03-22","cited_by_count":9,"area":null},{"id":"2403.16137","title":"A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective","created":"2024-03-24","cited_by_count":9,"area":null},{"id":"2408.12133","title":"Self-Supervised Representation Learning for Geospatial Objects: A Survey","created":"2024-08-22","cited_by_count":9,"area":null},{"id":"2207.11996","title":"Generative Subgraph Contrast for Self-Supervised Graph Representation Learning","created":"2022-07-25","cited_by_count":8,"area":null},{"id":"2405.04245","title":"Exploring Correlations of Self-Supervised Tasks for Graphs","created":"2024-05-07","cited_by_count":7,"area":null},{"id":"2312.14222","title":"Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning","created":"2023-12-21","cited_by_count":6,"area":null},{"id":"2402.01440","title":"A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learning","created":"2024-02-02","cited_by_count":6,"area":null},{"id":"2107.09787","title":"Group Contrastive Self-Supervised Learning on Graphs","created":"2021-07-20","cited_by_count":5,"area":null},{"id":"2112.08733","title":"Self-Supervised Dynamic Graph Representation Learning via Temporal Subgraph Contrast","created":"2021-12-16","cited_by_count":5,"area":null},{"id":"2205.15746","title":"Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning","created":"2022-05-31","cited_by_count":5,"area":null},{"id":"2210.16906","title":"DyG2Vec: Efficient Representation Learning for Dynamic Graphs","created":"2022-10-30","cited_by_count":5,"area":null},{"id":"2403.02719","title":"Multi-Scale Subgraph Contrastive Learning","created":"2024-03-05","cited_by_count":5,"area":null},{"id":"2404.12569","title":"Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data","created":"2024-04-19","cited_by_count":5,"area":null},{"id":"2201.10069","title":"Link Prediction with Contextualized Self-Supervision","created":"2022-01-25","cited_by_count":4,"area":null},{"id":"2205.13038","title":"Improving Subgraph Representation Learning via Multi-View Augmentation","created":"2022-05-25","cited_by_count":4,"area":null},{"id":"2207.01792","title":"Features Based Adaptive Augmentation for Graph Contrastive Learning","created":"2022-07-05","cited_by_count":4,"area":null},{"id":"2308.03271","title":"Local Structure-aware Graph Contrastive Representation Learning","created":"2023-08-07","cited_by_count":4,"area":null},{"id":"2303.06213","title":"CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network","created":"2023-03-10","cited_by_count":3,"area":null},{"id":"2308.16441","title":"Contrastive Representation Learning Based on Multiple Node-centered Subgraphs","created":"2023-08-31","cited_by_count":3,"area":null},{"id":"2410.15247","title":"Tensor-Fused Multi-View Graph Contrastive Learning","created":"2024-10-20","cited_by_count":3,"area":null},{"id":"2506.08326","title":"Graph Prompting for Graph Learning Models: Recent Advances and Future Directions","created":"2025-06-10","cited_by_count":3,"area":null},{"id":"2209.00508","title":"Models and Benchmarks for Representation Learning of Partially Observed Subgraphs","created":"2022-09-01","cited_by_count":2,"area":null},{"id":"2209.13556","title":"Contrast Pattern Mining: A Survey","created":"2022-09-27","cited_by_count":2,"area":null},{"id":"2210.12506","title":"Self-supervised Graph-based Point-of-interest Recommendation","created":"2022-10-22","cited_by_count":2,"area":null},{"id":"2401.03638","title":"Unifying Graph Contrastive Learning via Graph Message Augmentation","created":"2024-01-08","cited_by_count":2,"area":null},{"id":"2503.10100","title":"SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning","created":"2025-03-13","cited_by_count":2,"area":null},{"id":"2106.15467","title":"Few-Shot Electronic Health Record Coding through Graph Contrastive Learning","created":"2021-06-29","cited_by_count":1,"area":null},{"id":"2107.02639","title":"Multi-Level Graph Contrastive Learning","created":"2021-07-06","cited_by_count":1,"area":null},{"id":"2212.02679","title":"Self-supervised Graph Representation Learning for Black Market Account Detection","created":"2022-12-06","cited_by_count":1,"area":null},{"id":"2309.02304","title":"Graph Self-Contrast Representation Learning","created":"2023-09-05","cited_by_count":1,"area":null},{"id":"2402.09600","title":"Graph Contrastive Learning with Low-Rank Regularization and Low-Rank Attention for Noisy Node Classification","created":"2024-02-14","cited_by_count":1,"area":null},{"id":"2502.16233","title":"Graph Self-Supervised Learning with Learnable Structural and Positional Encodings","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2502.20885","title":"A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning","created":"2025-02-28","cited_by_count":1,"area":null},{"id":"2510.16311","title":"Toward General Digraph Contrastive Learning: A Dual Spatial Perspective","created":"2025-10-18","cited_by_count":1,"area":null},{"id":"2201.12843","title":"Graph Representation Learning via Aggregation Enhancement","created":"2022-01-30","cited_by_count":0,"area":null},{"id":"2210.12020","title":"HCL: Improving Graph Representation with Hierarchical Contrastive Learning","created":"2022-10-21","cited_by_count":0,"area":null},{"id":"2210.15120","title":"Federated Graph Representation Learning using Self-Supervision","created":"2022-10-27","cited_by_count":0,"area":null},{"id":"2303.15182","title":"Hybrid Augmented Automated Graph Contrastive Learning","created":"2023-03-24","cited_by_count":0,"area":null},{"id":"2306.03506","title":"Subgraph Networks Based Contrastive Learning","created":"2023-06-06","cited_by_count":0,"area":null},{"id":"2306.04004","title":"Randomized Schur Complement Views for Graph Contrastive Learning","created":"2023-06-06","cited_by_count":0,"area":null},{"id":"2402.10468","title":"Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation","created":"2024-02-16","cited_by_count":0,"area":null},{"id":"2409.05573","title":"Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2409.19117","title":"Range-aware Positional Encoding via High-order Pretraining: Theory and Practice","created":"2024-09-27","cited_by_count":0,"area":null},{"id":"2501.14694","title":"Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection","created":"2025-01-24","cited_by_count":0,"area":null},{"id":"2504.11321","title":"Subset-Contrastive Multi-Omics Network Embedding","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2505.23529","title":"Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning","created":"2025-05-29","cited_by_count":0,"area":null},{"id":"2509.02803","title":"A Graph Laplacian Eigenvector-based Pre-training Method for Graph Neural Networks","created":"2025-09-02","cited_by_count":0,"area":null},{"id":"2512.00716","title":"Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift","created":"2025-11-30","cited_by_count":0,"area":null},{"id":"2605.12685","title":"A Unified Perspective for Learning Graph Representations Across Multi-Level Abstractions","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2608.04381","title":"NodeJEPA: Structure-Conditioned Latent Prediction for Node-Level Graph Self-Supervised Learning","created":"2026-08-05","cited_by_count":0,"area":null}],"next_cursor":null}