BEGIN:VCALENDAR
VERSION:2.0
PRODID:researchseminars.org
CALSCALE:GREGORIAN
X-WR-CALNAME:researchseminars.org
BEGIN:VEVENT
SUMMARY:Kyle Cranmer (NYU)
DTSTART:20200702T163000Z
DTEND:20200702T173000Z
DTSTAMP:20260423T003254Z
UID:MPML/6
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/MPML/6/">On 
 the Interplay between Physics and Deep Learning.</a>\nby Kyle Cranmer (NYU
 ) as part of Mathematics\, Physics and Machine Learning (IST\, Lisbon)\n\n
 \nAbstract\nThe interplay between physics and deep learning is typically d
 ivided into two themes.\nThe first is “physics for deep learning”\, wh
 ere techniques from physics are brought to bear on understanding dynamics 
 of learning. The second is “deep learning for physics\,” which focuses
  on application of deep learning techniques to physics problems. I will pr
 esent a more nuanced view of this interplay with examples of how the struc
 ture of physics problems have inspired advances in deep learning and how i
 t yields insights on topics such as inductive bias\, interpretability\, an
 d causality.\n
LOCATION:https://researchseminars.org/talk/MPML/6/
END:VEVENT
END:VCALENDAR