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SUMMARY:Deep learning for wavefunctions (3) - Alex Matthews (DeepMind & TC
 M)
DTSTART:20250224T100000Z
DTEND:20250224T110000Z
UID:TALK225805@talks.cam.ac.uk
CONTACT:Nigel Cooper
DESCRIPTION:See the "TCM graduate teaching page":https://www.tcm.phy.cam.a
 c.uk/impact/teaching.html for further information.\n\n\nIn this series of 
 graduate lectures we will study the application of deep neural networks to
  the approximation of wavefunctions. Since 2017 there has been a surge of 
 interest in this area and this looks set to accelerate. Knowledge of quant
 um mechanics will be assumed up to early graduate level but familiarity wi
 th deep neural networks is not essential.\n\nIn the first part of this lec
 ture we will discover self-attention which is a crucial component in many 
 modern advances for AI in general. We will then discuss the use of self-at
 tention for many electron systems.\nIn the second part of the lecture we w
 ill put what we have learned in context of the broader field of computatio
 nal quantum mechanics and reflect on open questions and potential extensio
 ns.
LOCATION:TCM Seminar Room (530)\, Cavendish Laboratory\, Department of Phy
 sics
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