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, ...

Knowing the stakes, Rose and her classmates at their west-side elementary practiced the drill just as their teacher instructed. The third graders kept a stack of worksheets tucked underneath their ...

Abstract: The success of pre-trained 2D vision models can largely be attributed to their ability to learn from large-scale datasets. However, compared with 2D image datasets, current pre-training data ...