Abstract
We present a neural approach for approximating the automorphism partitioning problem of a given graph. This approach combines the energy minimization process of neural networks for combinatorial optimization problems with simple group-theoretic properties. Neural networks are applied to rapidly find relevant automorphisms while group-theoretic information guides the search for these automorphisms.
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Jain, B.J., Wysotzki, F. Automorphism Partitioning with Neural Networks. Neural Processing Letters 17, 205–215 (2003). https://doi.org/10.1023/A:1023657727387
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DOI: https://doi.org/10.1023/A:1023657727387