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SUMMARY:Topical Seminar: Exploring Nuclear Physics through theoretical Mod
 els and Artificial Intelligence.
DTSTART;VALUE=DATE-TIME:20260513T090000Z
DTEND;VALUE=DATE-TIME:20260513T100000Z
DTSTAMP;VALUE=DATE-TIME:20260508T004932Z
UID:indico-event-8601@indico.ific.uv.es
DESCRIPTION:The study of nuclear structure and its evolution across the nu
 clear chart remains one of the most fundamental and challenging problems i
 n modern physics. Despite significant progress in theoretical modeling\, c
 ertain regions of the nuclear landscape\, particularly near the drip lines
  and among superheavy elements (SHE)\, continue to present substantial the
 oretical and experimental uncertainties.\n\nRecent advances in Artificial 
 Intelligence (AI) and Machine Learning (ML) offer a promising new paradigm
  for modeling complex physical systems by uncovering nonlinear correlation
 s embedded within nuclear data. These data-driven approaches have the pote
 ntial to complement\, and in some cases surpass\, computationally intensiv
 e many-body methods through improved inference\, uncertainty quantificatio
 n\, and the discovery of novel empirical relationships.\n\nIn this talk\, 
 I will present recent work carried out in this direction at Cochin Univers
 ity of Science and Technology\, Kerala\, India.\n\n \n\nhttps://indico.if
 ic.uv.es/event/8601/
LOCATION:Universe 1001-Primera-1-1-1 - Paterna. Seminario
URL:https://indico.ific.uv.es/event/8601/
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