{"total":21,"rows":[{"id":"2210.00102","title":"MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization","created":"2022-09-30","cited_by_count":31,"area":null},{"id":"2308.13490","title":"TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs","created":"2023-08-25","cited_by_count":16,"area":null},{"id":"2401.02949","title":"Graph2Tac: Online Representation Learning of Formal Math Concepts","created":"2024-01-05","cited_by_count":15,"area":null},{"id":"2306.15632","title":"Asynchronous Algorithmic Alignment with Cocycles","created":"2023-06-27","cited_by_count":13,"area":null},{"id":"2406.03569","title":"GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications","created":"2024-06-05","cited_by_count":10,"area":null},{"id":"2308.10737","title":"UGSL: A Unified Framework for Benchmarking Graph Structure Learning","created":"2023-08-21","cited_by_count":9,"area":null},{"id":"2502.15054","title":"GiGL: Large-Scale Graph Neural Networks at Snapchat","created":"2025-02-20","cited_by_count":8,"area":null},{"id":"2406.06022","title":"GraphStorm: all-in-one graph machine learning framework for industry applications","created":"2024-06-10","cited_by_count":7,"area":null},{"id":"2311.18588","title":"Optimizing ZX-Diagrams with Deep Reinforcement Learning","created":"2023-11-30","cited_by_count":6,"area":null},{"id":"2409.08658","title":"Promoting Fairness in Link Prediction with Graph Enhancement","created":"2024-09-13","cited_by_count":6,"area":null},{"id":"2305.02577","title":"Text Reading Order in Uncontrolled Conditions by Sparse Graph Segmentation","created":"2023-05-04","cited_by_count":5,"area":null},{"id":"2403.05752","title":"Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling","created":"2024-03-09","cited_by_count":5,"area":null},{"id":"2212.04537","title":"Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks","created":"2022-12-08","cited_by_count":4,"area":null},{"id":"2407.15320","title":"Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence","created":"2024-07-07","cited_by_count":3,"area":null},{"id":"2502.00944","title":"Training speedups via batching for geometric learning: an analysis of static and dynamic algorithms","created":"2025-02-02","cited_by_count":2,"area":null},{"id":"2301.04824","title":"A Network Science perspective of Graph Convolutional Networks: A survey","created":"2023-01-12","cited_by_count":1,"area":null},{"id":"2411.01109","title":"Optimization of GNN Training Through Half-precision","created":"2024-11-02","cited_by_count":1,"area":null},{"id":"2411.11375","title":"Graph Neural Networks on Graph Databases","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2311.06192","title":"Greedy PIG: Adaptive Integrated Gradients","created":"2023-11-10","cited_by_count":0,"area":null},{"id":"2408.12753","title":"Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks","created":"2024-08-22","cited_by_count":0,"area":null},{"id":"2411.02645","title":"Fine Grained Insider Risk Detection","created":"2024-11-04","cited_by_count":0,"area":null}],"next_cursor":null}