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Found 2 papers, 1 papers with code
Faithful Explanations for Deep Graph Models
Second, our analytical and empirical results demonstrate that feature attribution methods cannot capture the nonlinear effect of edge features, while existing subgraph explanation methods are not faithful.
GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing
Careful placement of a computational application within a target device cluster is critical for achieving low application completion time.
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