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 seismic inversion, the subsurface model can be parameterized by a truncated Fourier series, and then, the inversion problem is the inversion of the Fourier coefficients. To improve the ...
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