{"total":16,"rows":[{"id":"2112.03968","title":"Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks","created":"2021-12-07","cited_by_count":51,"area":null},{"id":"2110.02753","title":"Semi-relaxed Gromov-Wasserstein divergence with applications on graphs","created":"2021-10-06","cited_by_count":21,"area":null},{"id":"2107.10234","title":"Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks","created":"2021-07-21","cited_by_count":19,"area":null},{"id":"2210.09809","title":"Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel","created":"2022-10-18","cited_by_count":8,"area":null},{"id":"2110.04060","title":"New Insights into Graph Convolutional Networks using Neural Tangent Kernels","created":"2021-10-08","cited_by_count":4,"area":null},{"id":"2310.10374","title":"Multi-Factor Spatio-Temporal Prediction based on Graph Decomposition Learning","created":"2023-10-16","cited_by_count":4,"area":null},{"id":"2111.03317","title":"Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters","created":"2021-11-05","cited_by_count":1,"area":null},{"id":"2108.09637","title":"Graph-Convolutional Deep Learning to Identify Optimized Molecular Configurations","created":"2021-08-22","cited_by_count":0,"area":null},{"id":"2307.01389","title":"Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference","created":"2023-07-03","cited_by_count":0,"area":null},{"id":"2312.14847","title":"Large Scale Training of Graph Neural Networks for Optimal Markov-Chain Partitioning Using the Kemeny Constant","created":"2023-12-22","cited_by_count":0,"area":null},{"id":"2402.03025","title":"Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation","created":"2024-02-05","cited_by_count":0,"area":null},{"id":"2402.07340","title":"Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks","created":"2024-02-12","cited_by_count":0,"area":null},{"id":"2405.03650","title":"Generated Contents Enrichment","created":"2024-05-06","cited_by_count":0,"area":null},{"id":"2410.14604","title":"Learning to Control the Smoothness of Graph Convolutional Network Features","created":"2024-10-18","cited_by_count":0,"area":null},{"id":"2505.14005","title":"Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks","created":"2025-05-20","cited_by_count":0,"area":null},{"id":"2605.28488","title":"Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Models","created":"2026-05-27","cited_by_count":0,"area":null}],"next_cursor":null}