270 citations · 3.2k across the 56 of their papers we have counts for
58 papers
Bayesian Renormalization
David S. Berman, Marc S. Klinger, Alexander G. Stapleton
In this note we present a fully information theoretic approach to renormalization inspired by Bayesian statistical inference, which we refer to as Bayesian Renormalization. The mai…
The Inverse of Exact Renormalization Group Flows as Statistical Inference
David S. Berman, Marc S. Klinger
We build on the view of the Exact Renormalization Group (ERG) as an instantiation of Optimal Transport described by a functional convection-diffusion equation. We provide a new inf…
Twisted Self-duality
David S. Berman, Tancredi Schettini Gherardini
We examine a generalisation of the usual self-duality equations for Yang-Mills theory when the colour space admits a non-trivial involution. This involution allows us to construct…
On the Dynamics of Inference and Learning
David S. Berman, Jonathan J. Heckman, Marc Klinger
Statistical Inference is the process of determining a probability distribution over the space of parameters of a model given a data set. As more data becomes available this probabi…
Double copying Exceptional Field theories
David S. Berman, Kwangeon Kim, Kanghoon Lee
We examine exceptional field theory through the lens of the generalised double copy formalism. This allows us to construct classical solutions in M-theory using a generalised Kerr-…
Machine Learning Calabi-Yau Hypersurfaces
David S. Berman, Yang-Hui He, Edward Hirst
We revisit the classic database of weighted-P4s which admit Calabi-Yau 3-fold hypersurfaces equipped with a diverse set of tools from the machine-learning toolbox. Unsupervised tec…