{"total":15,"rows":[{"id":"2402.03358","title":"A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation","created":"2024-01-29","cited_by_count":57,"area":null},{"id":"2102.01350","title":"Graph Coarsening with Neural Networks","created":"2021-02-02","cited_by_count":55,"area":null},{"id":"2211.08854","title":"Graph Filters for Signal Processing and Machine Learning on Graphs","created":"2022-11-16","cited_by_count":53,"area":null},{"id":"2106.11863","title":"Graph coarsening: From scientific computing to machine learning","created":"2021-06-22","cited_by_count":21,"area":null},{"id":"2402.10634","title":"Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling","created":"2024-02-16","cited_by_count":17,"area":null},{"id":"2104.04710","title":"Pyramidal Reservoir Graph Neural Network","created":"2021-04-10","cited_by_count":10,"area":null},{"id":"2210.00437","title":"A Unified Framework for Optimization-Based Graph Coarsening","created":"2022-10-02","cited_by_count":9,"area":null},{"id":"2412.13842","title":"Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training","created":"2024-12-18","cited_by_count":9,"area":null},{"id":"2208.03523","title":"Generalizing Downsampling from Regular Data to Graphs","created":"2022-08-06","cited_by_count":6,"area":null},{"id":"2409.05100","title":"MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks","created":"2024-09-08","cited_by_count":5,"area":null},{"id":"2103.06126","title":"Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction","created":"2021-03-10","cited_by_count":2,"area":null},{"id":"2311.06557","title":"Identification of vortex in unstructured mesh with graph neural networks","created":"2023-11-11","cited_by_count":1,"area":null},{"id":"2402.12407","title":"Accelerating local laplacian filters on FPGAs","created":"2024-02-18","cited_by_count":0,"area":null},{"id":"2509.14836","title":"Sampling Method for Generalized Graph Signals with Pre-selected Vertices via DC Optimization","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2609.26603","title":"Hierarchical GNNs for power flow: letting physics shape the hierarchy","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}