Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
Abstract: In recent years, deep learning-based methods have attracted much attention and achieved remarkable results for intelligent fault diagnosis of rotating machinery. However, in many actual ...
O projeto mede e compara as duas estratégias (estados explorados, validações, podas e tempo) sobre sete instâncias e gera gráficos para a documentação. Disciplina: Fundamentos de Projeto e Análise de ...
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