{"total":38,"rows":[{"id":"2202.08235","title":"Data Augmentation for Deep Graph Learning: A Survey","created":"2022-02-16","cited_by_count":133,"area":null},{"id":"2310.04987","title":"Data-centric Graph Learning: A Survey","created":"2023-10-08","cited_by_count":22,"area":null},{"id":"2208.09779","title":"Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation","created":"2022-08-21","cited_by_count":12,"area":null},{"id":"2303.04040","title":"Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks","created":"2023-03-07","cited_by_count":12,"area":null},{"id":"2410.17555","title":"FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning","created":"2024-10-23","cited_by_count":8,"area":null},{"id":"2410.01669","title":"Sparse Covariance Neural Networks","created":"2024-10-02","cited_by_count":7,"area":null},{"id":"2405.15218","title":"AGS-GNN: Attribute-guided Sampling for Graph Neural Networks","created":"2024-05-24","cited_by_count":6,"area":null},{"id":"2305.13115","title":"Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention","created":"2023-05-22","cited_by_count":5,"area":null},{"id":"2204.02027","title":"A Survey on Dropout Methods and Experimental Verification in Recommendation","created":"2022-04-05","cited_by_count":4,"area":null},{"id":"2208.03559","title":"Triple Sparsification of Graph Convolutional Networks without Sacrificing the Accuracy","created":"2022-08-06","cited_by_count":4,"area":null},{"id":"2312.10903","title":"Robust Node Representation Learning via Graph Variational Diffusion Networks","created":"2023-12-18","cited_by_count":4,"area":null},{"id":"2504.14847","title":"Reliable Multi-Modal Object Re-Identification via Modality-Aware Graph Reasoning","created":"2025-04-21","cited_by_count":4,"area":null},{"id":"2207.10941","title":"Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect","created":"2022-07-22","cited_by_count":3,"area":null},{"id":"2209.13539","title":"Spiking GATs: Learning Graph Attentions via Spiking Neural Network","created":"2022-09-05","cited_by_count":3,"area":null},{"id":"2210.10946","title":"Causally-guided Regularization of Graph Attention Improves Generalizability","created":"2022-10-20","cited_by_count":3,"area":null},{"id":"2312.05479","title":"Exploring Sparsity in Graph Transformers","created":"2023-12-09","cited_by_count":3,"area":null},{"id":"2506.06917","title":"Graph-Based Physics-Guided Urban PM2.5 Air Quality Imputation with Constrained Monitoring Data","created":"2025-06-07","cited_by_count":3,"area":null},{"id":"2311.12823","title":"EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification","created":"2023-09-28","cited_by_count":2,"area":null},{"id":"2111.05694","title":"LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs","created":"2021-11-10","cited_by_count":1,"area":null},{"id":"2212.01749","title":"Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification","created":"2022-12-04","cited_by_count":1,"area":null},{"id":"2504.20666","title":"SFi-Former: Sparse Flow Induced Attention for Graph Transformer","created":"2025-04-29","cited_by_count":1,"area":null},{"id":"2511.08888","title":"Weaver: Kronecker Product Approximations of Spatiotemporal Attention for Traffic Network Forecasting","created":"2025-11-12","cited_by_count":1,"area":null},{"id":"2211.15081","title":"Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation","created":"2022-11-28","cited_by_count":0,"area":null},{"id":"2303.01193","title":"Interpretable System Identification and Long-term Prediction on Time-Series Data","created":"2023-03-02","cited_by_count":0,"area":null},{"id":"2405.12724","title":"RemoCap: Disentangled Representation Learning for Motion Capture","created":"2024-05-21","cited_by_count":0,"area":null},{"id":"2406.14846","title":"Graph Edge Representation via Tensor Product Graph Convolutional Representation","created":"2024-06-21","cited_by_count":0,"area":null},{"id":"2412.11964","title":"BetaExplainer: A Probabilistic Method to Explain Graph Neural Networks","created":"2024-12-16","cited_by_count":0,"area":null},{"id":"2503.12157","title":"Weighted Graph Structure Learning with Attention Denoising for Node Classification","created":"2025-03-15","cited_by_count":0,"area":null},{"id":"2504.13540","title":"EG-Gaussian: Epipolar Geometry and Graph Network Enhanced 3D Gaussian Splatting","created":"2025-04-18","cited_by_count":0,"area":null},{"id":"2506.00424","title":"COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning","created":"2025-05-31","cited_by_count":0,"area":null},{"id":"2506.16096","title":"A Brain-to-Population Graph Learning Framework for Diagnosing Brain Disorders","created":"2025-06-19","cited_by_count":0,"area":null},{"id":"2508.07659","title":"Discovering Spatial Correlations of Earth Observations for weather forecasting by using Graph Structure Learning","created":"2025-08-11","cited_by_count":0,"area":null},{"id":"2508.10425","title":"HiRef: Leveraging Hierarchical Ontology and Network Refinement for Robust Medication Recommendation","created":"2025-08-14","cited_by_count":0,"area":null},{"id":"2512.12410","title":"A Graph Attention Network-Based Framework for Reconstructing Missing LiDAR Beams","created":"2025-12-13","cited_by_count":0,"area":null},{"id":"2604.24293","title":"Latent-Hysteresis Graph ODEs: Modeling Coupled Topology-Feature Evolution via Continuous Phase Transitions","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2606.30101","title":"SIR: Structured Image Representations for Explainable Robot Learning","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2609.26737","title":"Diffusion-Induced Spatial Attention Overlapping Community Detection","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.31466","title":"Scaffold: Support Graph Theory Based Sparsification for Graph Neural Networks","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}