Abstract: Graph neural networks (GNNs) have demonstrated success as surrogate models for fluid simulations with smoothly varying dynamics, but their efficacy for discrete element method (DEM) ...
Abstract: Linking time-varying functional brain activity with underlying neural architecture remains a complex and challenging endeavor. A recent framework for this undertaking is graph signal ...
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