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LOCATION:501-502
DTSTART;TZID=America/Denver:20231113T161000
DTEND;TZID=America/Denver:20231113T163000
UID:submissions.supercomputing.org_SC23_sess440_ws_ai4s118@linklings.com
SUMMARY:Toward Rapid Autonomous Electron Microscopy with Active Meta-Learn
 ing
DESCRIPTION:Gayathri Saranathan, Martin Foltin, and Aalap Tripathy (Hewlet
 t Packard Enterprise (HPE)); Maxim Ziatdinov (Oak Ridge National Laborator
 y (ORNL)); Ann Mary Justine Koomthanam and Suparna Bhattacharya (Hewlett P
 ackard Enterprise (HPE)); Ayana Ghosh and Kevin Roccapriore (Oak Ridge Nat
 ional Laboratory (ORNL)); and Sreenivas Rangan Sukumar and Paolo Farabosch
 i (Hewlett Packard Enterprise (HPE))\n\nIn this work, we developed a metho
 d to accelerate computational steering of microscopy experiments by active
  meta-learning. Before this work, a tailored AI model was trained specific
 ally for every experiment by active learning to reconstruct spectrum and u
 ncover regions of interest by sampling just a few locations of the image. 
 Training individual models for each experiment may result in scalability c
 hallenges when dealing with high resolutions data, and complex structure-p
 roperty relationships often demand deeper AI models. A Reptile algorithm, 
 a first-order, model-agnostic meta-learning approach is used to train on i
 mages from prior experiments at different conditions such that the trained
  model can adapt to new unseen conditions in considerably less time. We ob
 serve up to ~30-40% reduction in the number of training epochs for active 
 learning exploration. The benefit for structure-property investigation for
  spectral reconstruction of STEM EELS nanoparticle plasmonic images is dem
 onstrated across multiple experiments.\n\nTag: Artificial Intelligence/Mac
 hine Learning\n\nRegistration Category: Workshop Reg Pass\n\nSession Chair
 s: Murali Emani (Argonne National Laboratory (ANL)); Gokcen Kestor (Barcel
 ona Supercomputing Center (BSC); University of California, Merced); and Do
 ng Li (University of California, Merced)\n\n
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