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Data Science, Artificial Intelligence and Machine Learning II

FOCUS · G13 · ID: 48670

Presentations

  • TBA

    ORAL · Invited

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    Presenters

    • Rupak Chatterjee

      Stevens Institute of Technology

    Authors

    • Rupak Chatterjee

      Stevens Institute of Technology

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  • TBA

    ORAL · Invited

    –

    Presenters

    • Kristin Persson

      Lawrence Berkeley National Laboratory

    Authors

    • Kristin Persson

      Lawrence Berkeley National Laboratory

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  • Ultra-Fast Force Fields (UF<sup>3</sup>) framework for machine-learning interatomic potentials

    ORAL

    –

    Publication: S. R. Xie, M. Rupp, and R. G. Hennig, "Ultra-fast interpretable machine-learning potentials", preprint arXiv:2110.00624 (2021).

    Presenters

    • Stephen R Xie

      Department of Materials Science and Engineering, University of Florida, KBR Inc., Intelligent Systems Division, NASA Ames Research Center, University of Florida

    Authors

    • Stephen R Xie

      Department of Materials Science and Engineering, University of Florida, KBR Inc., Intelligent Systems Division, NASA Ames Research Center, University of Florida

    • Robert Schmid

      Department of Computer and Information Science, University of Konstanz, Germany

    • Matthias Rupp

      Department of Computer and Information Science, University of Konstanz, Germany

    • Richard G. G Hennig

      University of Florida, Department of Materials Science and Engineering, University of Florida, Department of Materials Science and Engineering, University of Florida, Gainesville, Florida 32611, United States

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  • MaterialEyes: Utilizing literature to characterize materials from images

    ORAL

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    Publication: [1] https://github.com/MaterialEyes/exsclaim<br>[2] E Schwenker, W Jiang, T Spreadbury, N Ferrier, O Cossairt, MKY Chan, "EXSCLAIM!--An automated pipeline for the construction of labeled materials imaging datasets from literature," arXiv preprint arXiv:2103.10631. <br>[3] W Jiang, E Schwenker, T Spreadbury, N Ferrier, MKY Chan, O Cossairt, "A Two-stage Framework for Compound Figure Separation," 2021 IEEE International Conference on Image Processing (ICIP), DOI: 10.1109/ICIP42928.2021.9506171.<br>[4] W Jiang, E Schwenker, T Spreadbury, K Li, MKY Chan, O Cossairt, "Plot2Spectra: an Automatic Spectra Extraction Tool," arXiv preprint arXiv:2107.02827.

    Presenters

    • Weixin Jiang

      Northwestern University

    Authors

    • Weixin Jiang

      Northwestern University

    • Eric Schwenker

      Argonne National Laboratory

    • Trevor Spreadbury

      Argonne National Laboratory

    • Oliver Cossairt

      Northwestern University

    • Maria K Chan

      Argonne National Laboratory

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  • Discovering Conservation Laws via Manifold Learning

    ORAL

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    Presenters

    • Peter Y Lu

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    Authors

    • Peter Y Lu

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    • Rumen Dangovski

      Massachusetts Institute of Technology

    • Marin Soljačić

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

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  • Deep Learning for Bayesian Optimization of High-Dimensional Scientific Problems

    ORAL

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    Publication: Kim, S., Lu, P. Y., Loh, C., Smith, J., Snoek, J., & Soljačić, M. (2021). Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. arXiv preprint arXiv:2104.11667.

    Presenters

    • Samuel Kim

      Massachusetts Institute of Technology MIT

    Authors

    • Samuel Kim

      Massachusetts Institute of Technology MIT

    • Peter Y Lu

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    • Charlotte Loh

      Massachusetts Institute of Technology MIT

    • Marin Soljačić

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    • Jasper Snoek

      Google Research

    • Jamie Smith

      Google Research

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  • Finite Element Network Analysis of the static response of 1D and 2D Structures

    ORAL

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    Publication: Jokar, M. and Semperlotti, F., 2021. Finite element network analysis: A machine learning based computational framework for the simulation of physical systems. Computers & Structures, 247, p.106484. <br>Jokar, M. and Semperlotti, F., "Two-Dimensional Finite Element Network Analysis: Formulation and Static Analysis of Structural Assemblies", under review in Computers & structures. <br>

    Presenters

    • Mehdi Jokar

      Purdue University, School of Mechanical Engineering, Ray W. Herrick Laboratories, Purdue University, West Lafayette, IN

    Authors

    • Mehdi Jokar

      Purdue University, School of Mechanical Engineering, Ray W. Herrick Laboratories, Purdue University, West Lafayette, IN

    • Fabio Semperlotti

      Purdue University, School of Mechanical Engineering, Ray W. Herrick Laboratories, Purdue University, West Lafayette, IN

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