{"total":37,"rows":[{"id":"2202.07179","title":"G-Mixup: Graph Data Augmentation for Graph Classification","created":"2022-02-15","cited_by_count":146,"area":null},{"id":"2103.05045","title":"Size-Invariant Graph Representations for Graph Classification Extrapolations","created":"2021-03-08","cited_by_count":84,"area":null},{"id":"2205.15117","title":"OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs","created":"2022-05-30","cited_by_count":38,"area":null},{"id":"2310.04987","title":"Data-centric Graph Learning: A Survey","created":"2023-10-08","cited_by_count":22,"area":null},{"id":"2211.03329","title":"Implicit Graphon Neural Representation","created":"2022-11-07","cited_by_count":19,"area":null},{"id":"2303.16458","title":"When to Pre-Train Graph Neural Networks? From Data Generation Perspective!","created":"2023-03-29","cited_by_count":18,"area":null},{"id":"2312.13583","title":"Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns","created":"2023-12-21","cited_by_count":13,"area":null},{"id":"2511.05592","title":"GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning","created":"2025-11-05","cited_by_count":13,"area":null},{"id":"2209.08223","title":"Joint Network Topology Inference via a Shared Graphon Model","created":"2022-09-17","cited_by_count":11,"area":null},{"id":"2410.17464","title":"Scalable Implicit Graphon Learning","created":"2024-10-22","cited_by_count":9,"area":null},{"id":"2308.15728","title":"Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials","created":"2023-08-30","cited_by_count":6,"area":null},{"id":"2105.14244","title":"Learning Graphon Autoencoders for Generative Graph Modeling","created":"2021-05-29","cited_by_count":5,"area":null},{"id":"2105.08678","title":"Nonparametric Modeling of Higher-Order Interactions via Hypergraphons","created":"2021-05-18","cited_by_count":4,"area":null},{"id":"2106.02803","title":"Network Estimation by Mixing: Adaptivity and More","created":"2021-06-05","cited_by_count":4,"area":null},{"id":"2306.01310","title":"EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost","created":"2023-06-02","cited_by_count":3,"area":null},{"id":"2307.13206","title":"Transferability of Graph Neural Networks using Graphon and Sampling Theories","created":"2023-07-25","cited_by_count":3,"area":null},{"id":"2407.13251","title":"Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection","created":"2024-07-18","cited_by_count":3,"area":null},{"id":"2407.21742","title":"HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection","created":"2024-07-31","cited_by_count":3,"area":null},{"id":"2409.09858","title":"A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View","created":"2024-09-15","cited_by_count":3,"area":null},{"id":"2304.03590","title":"Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels","created":"2023-04-07","cited_by_count":2,"area":null},{"id":"2406.06014","title":"Network two-sample test for block models","created":"2024-06-10","cited_by_count":2,"area":null},{"id":"2510.17515","title":"The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis","created":"2025-10-20","cited_by_count":2,"area":null},{"id":"2101.00503","title":"Modularity maximisation for graphons","created":"2021-01-02","cited_by_count":1,"area":null},{"id":"2202.05686","title":"Graphon-aided Joint Estimation of Multiple Graphs","created":"2022-02-11","cited_by_count":1,"area":null},{"id":"2408.03461","title":"When does the mean network capture the topology of a sample of networks?","created":"2024-08-06","cited_by_count":1,"area":null},{"id":"2510.05527","title":"Transfer Learning on Edge Connecting Probability Estimation under Graphon Model","created":"2025-10-07","cited_by_count":1,"area":null},{"id":"2602.16196","title":"Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning","created":"2026-02-18","cited_by_count":1,"area":null},{"id":"2102.02741","title":"Hawkes Processes on Graphons","created":"2021-02-04","cited_by_count":0,"area":null},{"id":"2404.08376","title":"Graph data augmentation with Gromow-Wasserstein Barycenters","created":"2024-04-12","cited_by_count":0,"area":null},{"id":"2502.00038","title":"The Spectral Barycentre of a Set of Graphs with Community Structure","created":"2025-01-26","cited_by_count":0,"area":null},{"id":"2506.06212","title":"Model-Driven Graph Contrastive Learning","created":"2025-06-06","cited_by_count":0,"area":null},{"id":"2508.12483","title":"Simultaneous estimation of connectivity and dimensionality in samples of networks","created":"2025-08-17","cited_by_count":0,"area":null},{"id":"2509.23230","title":"A Generative Model for Controllable Feature Heterophily in Graphs","created":"2025-09-27","cited_by_count":0,"area":null},{"id":"2510.03690","title":"From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning","created":"2025-10-04","cited_by_count":0,"area":null},{"id":"2603.15578","title":"Low-Complexity and Consistent Graphon Estimation from Multiple Networks","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2609.35620","title":"Attention Graphons: A Graph Limit Perspective on Graph Transformers","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.02439","title":"A Generative Model of Complex Networks Using Graphons and Neural Inverse Operators","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}