Deep Neural Networks as the Semi-classical Limit of Quantum Neural Networks

30 Jun 2020  ·  Marciano Antonino, Fabrocini Filippo, Greco Enrico, Terzidis Kostas ·

Our work intends to show that: (1) Quantum Neural Networks (QNN) can be mapped onto spin-networks, with the consequence that the level of analysis of their operation can be carried out on the side of Topological Quantum Field Theories (TQFT); (2) Deep Neural Networks (DNN) are a subcase of QNN, in the sense that they emerge as the semiclassical limit of QNN; (3) a number of Machine Learning (ML) key-concepts can be rephrased by using the terminology of TQFT. Our framework provides as well a working hypothesis for understanding the generalization behavior of DNN, relating it to the topological features of the graphs structures involved...

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Disordered Systems and Neural Networks General Relativity and Quantum Cosmology High Energy Physics - Theory Quantum Physics