nLab physical neural network

Contents

Context

Physics

physics, mathematical physics, philosophy of physics

Surveys, textbooks and lecture notes


theory (physics), model (physics)

experiment, measurement, computable physics

Contents

 Idea

A neural network which relies on a physical medium, such as a nonlinear? optical system, a mechanical plate oscillator, or an electronic? circuit?, to emulate neurons, rather than software? code?.

See also

 References

  • Logan G. Wright, Tatsuhiro Onodera, Martin M. Stein, Tianyu Wang, Darren T. Schachter, Zoey Hu & Peter L. McMahon, Deep physical neural networks trained with backpropagation, Nature 601, 549–555 (2022). doi:10.1038/s41586-021-04223-6. (web)

  • Victor Lopez-Pastor, Florian Marquardt, Self-learning Machines based on Hamiltonian Echo Backpropagation, (arXiv:2103.04992)

  • Sam Dillavou, Menachem Stern, Andrea J. Liu, Douglas J. Durian, Demonstration of Decentralized, Physics-Driven Learning, (arXiv:2108.00275)

Created on June 2, 2022 at 22:36:26. See the history of this page for a list of all contributions to it.