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VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Physics-enhanced machine learning with symmetry-adapted and long-r
 ange representations
DTSTART:20210702T160000
DTSTAMP:20260407T102723Z
UID:c09fd96fc36f2e052e5b923a1892f332aefb55af7678521bde2d53b6
CATEGORIES:Thesis defenses
DESCRIPTION:Andrea GRISAFI\nThesis Director: Prof. M. Ceriotti\,\nMaterial
 s Science and Engineering doctoral program\nThesis Nr. 8247\n\nTo take pa
 rt in the public defense\, please contact directly the speaker
LOCATION:
STATUS:CONFIRMED
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