We prove that any quantum field theory, or more generally any probability distribution over tempered distributions in $\mathbb{R}^d$, admits a neural network description with a countable infinity of parameters. As an example, we realize the $2d$ Liouville theory as a neural network and numerically compute the three-point function of vertex operators, finding agreement with the DOZZ formula.
Paper
References (6)
04To Appear in:2009
05BAYESIAN LEARNING FOR NEU-RAL NETWORKS1995