A game-level difficulty-aware curriculum learning framework for progressive graph neural network training in distribution network fault diagnosis
Abstract Graph neural networks (GNNs) have shown considerable potential for distribution network fault diagnosis; however, conventional empirical risk minimization with randomly ordered samples may lead to unstable convergence and substantial performance degradation when complex network topologies and severely corrupte...