All occurrences of this event have passed.
This listing is displayed for historical purposes.

Learning New Physics from a Machine

Raffaele D'Agnolo

I will discuss how to use neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The algorithm that I will describe returns a global p-value that quantifies the tension between the data and the reference model. It also allows to compare directly what the network has learned with the data, giving a fully transparent account of the nature of possible signals. The potential applications are broad, from LHC physics searches to cosmology and beyond.
Report Event As Inappropriate Contact Event Organizers

When and Where

Map Randall Laboratory - 3481

February 2019

12:00pm - 1:00pm

Explore Similar Events

  •  Loading Similar Events...