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Autonomous Systems

FOCUS · W13 · ID: 48665

Presentations

  • Domain-Aware Gaussian Processes and High-Performance Mathematical Optimization for Optimal Autonomous Data Acquisition

    ORAL · Invited

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    Publication: Marcus M Noack, Petrus H Zwart, Daniela M Ushizima, Masafumi Fukuto, Kevin G Yager,Katherine C Elbert, Christopher B Murray, Aaron Stein, Gregory S Doerk, Esther HRTsai, et al. Gaussian processes for autonomous data acquisition at large-scale synchrotron and neutron facilities. Nature Reviews Physics, pages 1–13, 2021.<br><br>Marcus M Noack and James A Sethian. Autonomous discovery in science and engineering.Technical report, USDOE Office of Science (SC)(United States), 2021.Marcus M Noack and James A Sethian. Advanced stationary and non-stationary kernel designs for domain-aware gaussian processes. arXiv preprint arXiv:2102.03432, 2021.<br><br>Marcus M Noack, Gregory S Doerk, Ruipeng Li, Masafumi Fukuto, and Kevin G Yager. Advances in kriging-based autonomous x-ray scattering experiments.Scientific reports,10(1):1–17, 2020.<br><br>Marcus M Noack, Gregory S Doerk, Ruipeng Li, Jason K Streit, Richard A Vaia, Kevin GYager, and Masafumi Fukuto. Autonomous materials discovery driven by gaussian process regression with inhomogeneous measurement noise and anisotropic kernels. Scientific reports, 10(1):1–16, 2020.

    Presenters

    • Marcus Noack

      Lawrence Berkeley National Laboratory, Lawrence Berkeley National Lab

    Authors

    • Marcus Noack

      Lawrence Berkeley National Laboratory, Lawrence Berkeley National Lab

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  • Quantum compiling by deep reinforcement learning

    ORAL · Invited

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    Publication: L. Moro , M. Paris, M. Restelli, E. Prati, Quantum Compiling via Deep Reinforcement Learning, Communications Physics 4, 178 (2021) DOI: 10.1038/s42005-021-00684-3

    Presenters

    • Enrico Prati

      Instito di Fotonica e Nanotechnologie

    Authors

    • Enrico Prati

      Instito di Fotonica e Nanotechnologie

    • Matteo Paris

      Università di Milano

    • Lorenzo Moro

      Politecnico di Milano

    • Marcello Restelli

      Politecnico di Milano

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  • Dynamic Manipulation of Ferroelectric Structures via Automated Piezoresponse Force Microscopy

    ORAL · Invited

    –

    Presenters

    • Kyle Kelley

      Oak Ridge National Laboratory, ornl, Oak Ridge National Lab

    Authors

    • Kyle Kelley

      Oak Ridge National Laboratory, ornl, Oak Ridge National Lab

    • Yongtao Liu

      Oak Ridge National Laboratory

    • Stephen Jesse

      Oak Ridge National Laboratory, University of Tennessee

    • Rama K Vasudevan

      Oak Ridge National Laboratory

    • Sergei V Kalinin

      Oak Ridge National Lab, Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge National Laboratory

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  • Active Learning-Driven Automated Scanning Probe Microscopy Enables Discovery of Structure-Property Relationship

    ORAL

    –

    Presenters

    • Yongtao Liu

      Oak Ridge National Laboratory

    Authors

    • Yongtao Liu

      Oak Ridge National Laboratory

    • Kyle Kelley

      Oak Ridge National Laboratory, ornl, Oak Ridge National Lab

    • Rama K Vasudevan

      Oak Ridge National Laboratory

    • Hiroshi Funakubo

      Tokyo Institute of Technology

    • Susan E Trolier-Mckinstry

      The Pennsylvania State University

    • Maxim Ziatdinov

      Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge National Laboratory, Oak Ridge National Lab

    • Sergei V Kalinin

      Oak Ridge National Lab, Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge National Laboratory

    View abstract →

  • Towards automating analysis of nonequilibrium X-ray Photon Correlation Spectroscopy with acquisition rate-limited time resolution

    ORAL

    –

    Presenters

    • Tatiana Konstantinova

      Brookhaven National Laboratory

    Authors

    • Tatiana Konstantinova

      Brookhaven National Laboratory

    • Lutz Wiegart

      Brookhaven National Laboratory

    • Maksim Rakitin

      Brookhaven National Laboratory

    • Anthony M DeGennaro

      Brookhaven National Laboratory

    • Andi Barbour

      NSLS-II, Brookhaven National Lab, Brookhaven National Laboratory, Brookhaven National Lab

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  • Adaptive tuning of the latent space of encoder-decoder convolutional neural networks for virtual 6D diagnostics of time-varying charged particle beams

    ORAL

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    Publication: A. Scheinker. "Adaptive Machine Learning for Time-Varying Systems: Low Dimensional Latent Space Tuning." arXiv preprint arXiv:2107.06207, 2021.<br>A. Scheinker, et al. "An adaptive approach to machine learning for compact particle accelerators." Scientific Reports 11.1, 1-11, 2021.

    Presenters

    • Alexander Scheinker

      Los Alamos Natl Lab

    Authors

    • Alexander Scheinker

      Los Alamos Natl Lab

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  • Autonomous anomaly detection in MeV ultrafast electron diffraction

    ORAL

    –

    Presenters

    • Mariana A Fazio

      University of New Mexico

    Authors

    • Mariana A Fazio

      University of New Mexico

    • Salvador Sosa Guitron

      University of New Mexico

    • Destry Monk

      University of New Mexico

    • Junjie Li

      Brookhaven National Laboratory

    • Marcus Babzien

      Brookhaven National Laboratory

    • Mikhail Fedurin

      Brookhaven National Laboratory

    • Mark A Palmer

      Brookhaven National Laboratory

    • Sandra G Biedron

      University of New Mexico, Element Aero

    • Manel Martínez-Ramón

      University of New Mexico

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  • Reinforcement learning and neutron scattering

    ORAL

    –

    Presenters

    • William Ratcliff

      GDS, National Institute of Standards and Tech, NIST

    Authors

    • William Ratcliff

      GDS, National Institute of Standards and Tech, NIST

    • Kate Meuse

      Cornell University

    • Jessica Opsahl-Ong

      Rice University

    • Paul Kienzle

      National Institute of Standards and Technology, NIST Center for Neutron Research, Gaithersburg, MD, NIST, National Institute of Standards and Technology

    View abstract →