BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Machine learning detects terminal singularities - Sara Veneziale\,
  Imperial College London
DTSTART:20240214T141500Z
DTEND:20240214T151500Z
UID:TALK211474@talks.cam.ac.uk
CONTACT:Holly Krieger
DESCRIPTION: In this talk\, I will describe recent work in the application
  of machine learning to explore questions in algebraic geometry\, specific
 ally in the context of the study of Q-Fano varieties. These are Q-factoria
 l terminal Fano varieties\, and they are the key players in the Minimal Mo
 del Program. In this work\, we ask and answer if machine learning can dete
 rmine if a toric Fano variety has terminal singularities. We build a high-
 accuracy neural network that detects this\, which has two consequences. Fi
 rstly\, it inspires the formulation and proof of a new global\, combinator
 ial criterion to determine if a toric variety of Picard rank two has termi
 nal singularities. Secondly\, the machine learning model is used directly 
 to give the first sketch of the landscape of Q-Fano varieties in dimension
  eight. This is joint work with Tom Coates and Al Kasprzyk.
LOCATION:CMS MR13
END:VEVENT
END:VCALENDAR