{"total":27,"rows":[{"id":"2101.10025","title":"A Review of Graph Neural Networks and Their Applications in Power Systems","created":"2021-01-25","cited_by_count":63,"area":null},{"id":"2205.10129","title":"Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions","created":"2022-05-16","cited_by_count":28,"area":null},{"id":"2102.06349","title":"Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems","created":"2021-02-12","cited_by_count":21,"area":null},{"id":"2109.03604","title":"Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids","created":"2021-09-08","cited_by_count":18,"area":null},{"id":"2103.03729","title":"Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network","created":"2021-03-05","cited_by_count":7,"area":null},{"id":"2103.14251","title":"Embedding Power Flow into Machine Learning for Parameter and State Estimation","created":"2021-03-26","cited_by_count":6,"area":null},{"id":"2111.08185","title":"Graph neural network-based fault diagnosis: a review","created":"2021-11-16","cited_by_count":5,"area":null},{"id":"2208.08485","title":"Complex-Value Spatio-temporal Graph Convolutional Neural Networks and its Applications to Electric Power Systems AI","created":"2022-08-17","cited_by_count":4,"area":null},{"id":"2107.02275","title":"PPGN: Physics-Preserved Graph Networks for Real-Time Fault Location in Distribution Systems with Limited Observation and Labels","created":"2021-07-05","cited_by_count":3,"area":null},{"id":"2309.09921","title":"A Heterogeneous Graph-Based Multi-Task Learning for Fault Event Diagnosis in Smart Grid","created":"2023-09-18","cited_by_count":3,"area":null},{"id":"2503.22721","title":"PowerGNN: A Topology-Aware Graph Neural Network for Electricity Grids","created":"2025-03-26","cited_by_count":3,"area":null},{"id":"2108.07060","title":"Detecting and interpreting faults in vulnerable power grids with machine learning","created":"2021-08-16","cited_by_count":2,"area":null},{"id":"2205.05250","title":"Spatial-temporal associations representation and application for process monitoring using graph convolution neural network","created":"2022-05-11","cited_by_count":1,"area":null},{"id":"2211.02930","title":"1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems","created":"2022-11-05","cited_by_count":1,"area":null},{"id":"2212.10454","title":"Wind Power Scenario Generation Using Graph Convolutional Generative Adversarial Network","created":"2022-12-19","cited_by_count":1,"area":null},{"id":"2303.00428","title":"Supporting Future Electrical Utilities: Using Deep Learning Methods in EMS and DMS Algorithms","created":"2023-03-01","cited_by_count":1,"area":null},{"id":"2304.14680","title":"Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs","created":"2023-04-28","cited_by_count":1,"area":null},{"id":"2406.17073","title":"Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks","created":"2024-06-24","cited_by_count":1,"area":null},{"id":"2604.20403","title":"Robustness of Spatio-temporal Graph Neural Networks for Fault Location in Partially Observable Distribution Grids","created":"2026-04-22","cited_by_count":1,"area":null},{"id":"2607.29293","title":"Assessing the Generalization of Graph Neural Networks for Fault Location Across Increasing Distributed Energy Resource Penetration Levels","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2303.00105","title":"Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation","created":"2023-02-28","cited_by_count":0,"area":null},{"id":"2312.11898","title":"Short-Term Multi-Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention-GCN-LSTM","created":"2023-12-19","cited_by_count":0,"area":null},{"id":"2503.05797","title":"A Multi-Scale Attention-Based Attack Diagnosis Mechanism for Parallel Cyber-Physical Attacks in Power Grids","created":"2025-03-03","cited_by_count":0,"area":null},{"id":"2510.03571","title":"Generalization of Graph Neural Network Models for Distribution Grid Fault Detection","created":"2025-10-03","cited_by_count":0,"area":null},{"id":"2602.24254","title":"FaultXformer: A Transformer-Encoder Based Fault Classification and Location Identification model in PMU-Integrated Active Electrical Distribution System","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2608.16494","title":"Graph Machine Learning: An Opportunity for Power Systems","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2609.28149","title":"EvEMTBench: An Open Benchmark for Machine Learning in Power System Protection","created":"2026-09-23","cited_by_count":0,"area":null}],"next_cursor":null}