Phase space sampling and inference from weighted events with autoregressive flows
Phase space sampling and inference from weighted events with autoregressive flows
We explore the use of autoregressive flows, a type of generative model with tractable likelihood, as a means of efficient generation of physical particle collider events. The usual maximum likelihood loss function is supplemented by an event weight, allowing for inference from event samples with variable, and even negative event …