BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Some applications of machine learning in active matter - Eric Vand
 en-Eijnden\, Courant Institute of Mathematical Sciences\, New York Univers
 ity
DTSTART:20241126T130000Z
DTEND:20241126T140000Z
UID:TALK220438@talks.cam.ac.uk
CONTACT:Balázs Németh
DESCRIPTION:Machine learning (ML) techniques are changing Science and Engi
 neering by offering ways to reconsider complex problems once thought intra
 ctable because of the curse of dimensionality. In this talk\, I will discu
 ss the impact of ML on applications from active matter. Specifically I wil
 l show how physics-informed neural networks (PINNs) can be used to analyze
  first-order phase transitions in non-equilibrium systems\, and how advanc
 es in generative modeling can be leveraged to characterize the breakup of 
 time-reversal symmetry (TRS) and calculate entropy production rates (EPRs)
  in active systems. I will also discuss how the standard modus operandi of
  ML must be adapted in the context of such applications when they come wit
 h models and no data (as opposed to data and no models)\, and thereby requ
 ire to use active learning strategies for data acquisition. 
LOCATION:Center for Mathematical Sciences\, Lecture room MR4
END:VEVENT
END:VCALENDAR