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Mystic: A Framework for Predictive Science
--client
psf
--show
pycon2013
--room Poster4 2199 --force
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Marks
Author(s):
Michael McKerns
Location
Poster-4
10
Date
mar Sun 17
Days Raw Files
Start
09:24
First Raw Start
10:11
Duration
00:05:00
Offset
0:47:57
End
09:29
Last Raw End
10:15
Chapters
00:00
Total cuts_time
3 min.
https://us.pycon.org/2013/schedule/presentation/186/
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Mystic_A_Framework_for_Predictive_Science.json
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Description:
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We have built a robust optimization framework (mystic) that lowers the barrier to solving complex problems in predictive science. mystic provides tools for constraining design space and targeting unique solutions, including suites of standard and statistical constraints, discrete math, uncertainty quantification, and symbolic math. mystic is built from the ground up to leverage parallel computing.
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production notes
pycon13-t4-014.dv
Apply:
10:11:57 - 10:15:50 ( 00:03:53 )
S:
10:11:57 -
E:
10:15:50
D:
00:03:53
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10:11:57
seconds: 0.0
Wall: 10:11:57
Duration
00:03:53
10:15:50
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Wall: 10:11:57
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