55 citations · 56 across the 5 of their papers we have counts for
5 papers
Learning Trivializing Flows in a theory from coarser lattices
David Albandea, Luigi Del Debbio, Pilar Hernández +3
The so-called trivializing flows were proposed to speed up Hybrid Monte Carlo simulations, where the Wilson flow was used as an approximation of a trivializing map, a transformatio…
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…
Machine Learning Trivializing Maps: A First Step Towards Understanding How Flow-Based Samplers Scale Up
Luigi Del Debbio, Joe Marsh Rossney, Michael Wilson
A trivializing map is a field transformation whose Jacobian determinant exactly cancels the interaction terms in the action, providing a representation of the theory in terms of a…
Efficient Modelling of Trivializing Maps for Lattice Theory Using Normalizing Flows: A First Look at Scalability
Luigi Del Debbio, Joe Marsh Rossney, Michael Wilson
General-purpose Markov Chain Monte Carlo sampling algorithms suffer from a dramatic reduction in efficiency as the system being studied is driven towards a critical point. Recently…