6 papers
Learning Topological Features of -invariants
Brandon Robinson, Shimal Harichurn, Fabian Ruehle +3
Machine learning and data analysis techniques have recently emerged as powerful tools for identifying patterns and formulating conjectures in mathematical research, most notably in…
A Tale of Two Compact Bosons
Christian Ferko, Vishnu Jejjala, Brandon Robinson
Neural network field theory (NN-FT) defines a field theory by a network architecture together with a probability density on its latent variables. For compact theories the local Gau…
Topological Effects in Neural Network Field Theory
Christian Ferko, James Halverson, Vishnu Jejjala +1
Neural network field theory formulates field theory as a statistical ensemble of fields defined by a network architecture and a density on its parameters. We extend the constructio…
Virasoro Symmetry in Neural Network Field Theories
Brandon Robinson
Neural Network Field Theories (NN-FTs) typically describe Generalized Free Fields that lack a local stress-energy tensor in two dimensions, obstructing the realization of Virasoro…
Conformal Defects in Neural Network Field Theories
Pietro Capuozzo, Brandon Robinson, Benjamin Suzzoni
Neural Network Field Theories (NN-FTs) represent a novel construction of arbitrary field theories, including those of conformal fields, through the specification of the network arc…
New punctures for six-dimensional compactifications
Fabio Apruzzi, Noppadol Mekareeya, Brandon Robinson +1
Six-dimensional superconformal field theories (SCFTs) give rise to four-dimensional (4d) ones when compactified on Riemann surfaces. In the case, this yields th…