10 citations · 15 across the 4 of their papers we have counts for
7 papers
Fermions and Supersymmetry in Neural Network Field Theories
Samuel Frank, James Halverson, Anindita Maiti +1
We introduce fermionic neural network field theories via Grassmann-valued neural networks. Free theories are obtained by a generalization of the Central Limit Theorem to Grassmann…
Bayesian RG Flow in Neural Network Field Theories
Jessica N. Howard, Marc S. Klinger, Anindita Maiti +1
The Neural Network Field Theory correspondence (NNFT) is a mapping from neural network (NN) architectures into the space of statistical field theories (SFTs). The Bayesian renormal…
Wilsonian Renormalization of Neural Network Gaussian Processes
Jessica N. Howard, Ro Jefferson, Anindita Maiti +1
Separating relevant and irrelevant information is key to any modeling process or scientific inquiry. Theoretical physics offers a powerful tool for achieving this in the form of th…
Neural Network Field Theories: Non-Gaussianity, Actions, and Locality
Mehmet Demirtas, James Halverson, Anindita Maiti +2
Both the path integral measure in field theory and ensembles of neural networks describe distributions over functions. When the central limit theorem can be applied in the infinite…
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators
Anindita Maiti, Keegan Stoner, James Halverson
Parameter-space and function-space provide two different duality frames in which to study neural networks. We demonstrate that symmetries of network densities may be determined via…
Gravitational Waves from Dark Yang-Mills Sectors
James Halverson, Cody Long, Anindita Maiti +2
Dark Yang-Mills sectors, which are ubiquitous in the string landscape, may be reheated above their critical temperature and subsequently go through a confining first-order phase tr…