{"total":23,"rows":[{"id":"2406.00943","title":"State Space Models on Temporal Graphs: A First-Principles Study","created":"2024-06-03","cited_by_count":16,"area":null},{"id":"2410.17941","title":"Spiking Graph Neural Network on Riemannian Manifolds","created":"2024-10-23","cited_by_count":16,"area":null},{"id":"2404.07941","title":"SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning","created":"2024-03-11","cited_by_count":8,"area":null},{"id":"2303.12341","title":"EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning","created":"2023-03-22","cited_by_count":7,"area":null},{"id":"2305.19306","title":"A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks","created":"2023-05-30","cited_by_count":6,"area":null},{"id":"2405.16851","title":"Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning","created":"2024-05-27","cited_by_count":5,"area":null},{"id":"2410.06883","title":"Degree-Conscious Spiking Graph for Cross-Domain Adaptation","created":"2024-10-09","cited_by_count":5,"area":null},{"id":"2403.15480","title":"SpikeGraphormer: A High-Performance Graph Transformer with Spiking Graph Attention","created":"2024-03-21","cited_by_count":3,"area":null},{"id":"2412.09379","title":"Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning","created":"2024-12-12","cited_by_count":3,"area":null},{"id":"2502.16431","title":"UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs","created":"2025-02-23","cited_by_count":3,"area":null},{"id":"2508.02069","title":"SpikeSTAG: Spatial-Temporal Forecasting via GNN-SNN Collaboration","created":"2025-08-04","cited_by_count":3,"area":null},{"id":"2411.11259","title":"Graph Retention Networks for Dynamic Graphs","created":"2024-11-18","cited_by_count":2,"area":null},{"id":"2507.14069","title":"Edge Intelligence with Spiking Neural Networks","created":"2025-07-18","cited_by_count":2,"area":null},{"id":"2506.13099","title":"Dynamic Graph Condensation","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2601.12903","title":"Deep Temporal Graph Clustering: A Comprehensive Benchmark and Datasets","created":"2026-01-19","cited_by_count":1,"area":null},{"id":"2602.01124","title":"ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs","created":"2026-02-01","cited_by_count":1,"area":null},{"id":"2311.16605","title":"LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning","created":"2023-11-28","cited_by_count":0,"area":null},{"id":"2404.01897","title":"Continuous Spiking Graph Neural Networks","created":"2024-04-02","cited_by_count":0,"area":null},{"id":"2407.20508","title":"Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies","created":"2024-07-30","cited_by_count":0,"area":null},{"id":"2501.19069","title":"Improving vision-language alignment with graph spiking hybrid Networks","created":"2025-01-31","cited_by_count":0,"area":null},{"id":"2508.03598","title":"DyCAF-Net: Dynamic Class-Aware Fusion Network","created":"2025-08-05","cited_by_count":0,"area":null},{"id":"2602.12613","title":"Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2605.13863","title":"Neuromorphic Graph Anomaly Detection via Adaptive STDP and Spiking Graph Neural Networks","created":"2026-04-29","cited_by_count":0,"area":null}],"next_cursor":null}