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: Graph pooling plays a crucial role in achieving effective local information aggregation. When dealing with graph, data in non-Euclidean space, a major challenge lies in the uncertainty of ...
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