2
$\begingroup$

It's known that many problems (e.g. XOR) have the exact solutions represented by neural networks. The question is: What kind of graph theory problems can be solved using neural networks?

$\endgroup$

closed as unclear what you're asking by Andrej Bauer, Johannes Hahn, Stefan Kohl, Wolfgang, Pace Nielsen Feb 27 '18 at 17:01

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

  • 1
    $\begingroup$ Maybe neural networks can help shed a light on Hadwiger's conjecture. $\endgroup$ – Sylvain JULIEN Feb 24 '18 at 19:15
2
$\begingroup$

Here is an example that has found a real-world application, in the context of quantum error correction: The decoding of stabilizer codes is a problem of minimum weight-perfect matching on a graph (for the surface code or toric code) or a hypergraph (for the color code). Recurrent neural networks offer a performance that is comparable or better than existing algorithms. Some pointers to the literature:

$\endgroup$

Not the answer you're looking for? Browse other questions tagged or ask your own question.