Abstract: Graph neural networks (GNNs) have emerged as a powerful framework for a wide range of node-level graph learning tasks. However, their performance typically depends on random or minimally ...
Abstract: Neural operators, such as graph neural operators (GNOs) and Fourier neural operators (FNOs), directly learn the mapping from any functional parametric dependence to the solution and have ...
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