Speaker
Phiala Shanahan
(MIT)
Description
I will describe recent progress in the development of custom machine learning architectures based on flow models for the efficient sampling of gauge field configurations. I will present updates on the status of this program and outline the challenges and potential of the approach.
Primary authors
Phiala Shanahan
(MIT)
Ryan Abbott
(MIT)
Michael Albergo
(New York University)
Denis Boyda
(Argonne)
Kyle Cranmer
Dan Hackett
Gurtej Kanwar
(University of Bern)
Sebastian Racaniere
(Deep Mind)
Danilo Rezende
(Deep Mind)
Fernando Romero-Lopez
(MIT)
Julian Urban
(ITP Heidelberg)
