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Session
Presentation | S13D: Uncertainty Quantification in AI/ML Applications for Seismic Monitoring Poster
Poster
S13D-0223: Optimizing Seismological Objective Functions with Machine Learning: A Case Study with Focal Mechanism Determination
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Schedule
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Credits
Mon, Dec 15
Board 0223‚ Hall EFG (Poster Hall)
2:15pm - 5:45pm (Central)
NOLA CC
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Xiaohan Song
Stanford University
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Author(s):
Xiaohan Song
, Stanford University
(First Author, Presenting Author)
Men-Andrin Meier
, ETH Zurich
William Ellsworth
, Stanford University
Gregory Beroza
, Stanford University
View Abstract
Scientific Discipline
Seismology
Suggested Itineraries
Machine Learning and AI
Neighborhood
Earth Interior
Type
Poster
I Will Be at My Poster Time
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Main Session
Poster
S13D: Uncertainty Quantification in AI/ML Applications for Seismic Monitoring Poster
2:15pm-5:45pm Dec 15 (Central)
Maeva Pourpoint
Discussion
