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...

PDF Abstract
No code implementations yet. Submit your code now

Categories


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