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: Multimodal image-matching success rates (SRs) are often low due to nonlinear radiation differences. Furthermore, when geometric transformations such as rotation and resolution exist between ...
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