BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Finding the Needle in the Haystack: Machine Learning for Rare Even
 t Simulations - Professor Christoph Dellago\, University of Vienna
DTSTART:20240522T133000Z
DTEND:20240522T143000Z
UID:TALK208918@talks.cam.ac.uk
CONTACT:Lisa Masters
DESCRIPTION:The microscopic dynamics of many condensed matter systems occu
 rring in nature and technology is dominated by rare but important barrier 
 crossing events. Examples of such processes include nucleation at first or
 der phase transitions\, chemical reactions and the folding of biopolymers.
  The resulting wide ranges of time scales are a challenge for molecular si
 mulation and numerous simulation methods have been developed to address th
 is problem. Recently\, machine learning methods have been proposed as a po
 werful way to further enhance such simulations. In my talk\, I will discus
 s various machine learning approaches based on deep neural networks to sam
 ple rare reactive trajectories and identify the collective variable needed
  for the construction of low-dimensional models capturing the microscopic 
 mechanism.
LOCATION:Unilever Lecture Theatre\, Yusuf Hamied Department of Chemistry
END:VEVENT
END:VCALENDAR