A GNN framework learns spectral embeddings of sparse matrices to minimize a fill-in surrogate and produces competitive reorderings versus classical graph algorithms.
Technical Report, LaBRI, Université Bordeaux, Bordeaux, France (2020)
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Bridging the Gap between Sparse Matrix Reordering and Factorization: A Deep Learning Framework for Fill-in Reduction
A GNN framework learns spectral embeddings of sparse matrices to minimize a fill-in surrogate and produces competitive reorderings versus classical graph algorithms.