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Found 3 papers, 2 papers with code
Neural Network Field Theories: Non-Gaussianity, Actions, and Locality
Conversely, the correspondence allows one to engineer architectures realizing a given field theory by representing action deformations as deformations of neural network parameter densities.
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators
We demonstrate that symmetries of network densities may be determined via dual computations of network correlation functions, even when the density is unknown and the network is not equivariant.
Neural Networks and Quantum Field Theory
We propose a theoretical understanding of neural networks in terms of Wilsonian effective field theory.
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