138 citations · 1.2k across the 36 of their papers we have counts for
36 papers
Learning Trivializing Flows
David Albandea, Luigi Del Debbio, Pilar Hernández +3
The recent introduction of Machine Learning techniques, especially Normalizing Flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling effici…
Learning trivializing flows
David Albandea, Luigi Del Debbio, Pilar Hernández +3
The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling effici…
Protection against Cloning for Deep Learning
Richard Kenway
The susceptibility of deep learning to adversarial attack can be understood in the framework of the Renormalisation Group (RG) and the vulnerability of a specific network may be di…
Vulnerability of Deep Learning
Richard Kenway
The Renormalisation Group (RG) provides a framework in which it is possible to assess whether a deep-learning network is sensitive to small changes in the input data and hence pron…
Five-dimensional Gauge Theories in a warped background
Richard D. Kenway, Eliana Lambrou
The phase diagram of five-dimensional anisotropic gauge theories in a flat background has been extensively explored during the last decade. Here, we present novel results for the p…
Searching for a continuum 4D field theory arising from a 5D non-abelian gauge theory
Luigi Del Debbio, Richard D. Kenway, Eliana Lambrou +1
The anisotropic 5D SU(2) Yang-Mills model has been widely investigated on the lattice during the last decade. In the case where all dimensions are large in size, it was previously…