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Data Science III: Deep Learning

FOCUS · R20 · ID: 355165

Presentations

  • Exploring Organic Ferroelectrics Using Data-driven Approaches

    ORAL

    –

    Presenters

    • Ayana Ghosh

      Univ of Connecticut - Storrs, Materials Science and Engineering, University of Connecticut, University of Connecticut

    Authors

    • Ayana Ghosh

      Univ of Connecticut - Storrs, Materials Science and Engineering, University of Connecticut, University of Connecticut

    • Nicholas Lubbers

      Computer, Computational and Statistical Sciences, Information Sciences, Los Alamos National Laboratory, Computer Computational Statistical Sciences, Los Alamos National Laboratory

    • Serge M Nakhmanson

      Univ of Connecticut - Storrs

    • Jian-Xin Zhu

      Los Alamos National Laboratory, Los Alamos National Lab, Los Alamos Natl Lab, Theoretical Division, Los Alamos National Laboratory

    View abstract →

  • Deep Learning Model for Finding New Superconductors

    ORAL

    –

    Presenters

    • Tomohiko Konno

      National Institute of Information and Communications Technology

    Authors

    • Tomohiko Konno

      National Institute of Information and Communications Technology

    • Hodaka Kurokawa

      University of Tokyo

    • Fuyuki Nabeshima

      University of Tokyo, Dept. of Basic Science, Univ. of Tokyo, Univ of Tokyo

    • Yuki Sakishita

      University of Tokyo, Dept. of Basic Science, Univ. of Tokyo, Univ of Tokyo

    • Ryo Ogawa

      University of Tokyo, Dept. of Basic Sci., Univ. Tokyo

    • Iwao Hosako

      National Institute of Information and Communications Technology

    • Atsutaka Maeda

      University of Tokyo, Dept. of Basic Science, Univ. of Tokyo, Univ of Tokyo, Dept. of Basic Sci., Univ. Tokyo

    View abstract →

  • Deep Learning for Energetic Materials: Predicting Material Properties from Electronic Structure using Convolutional Neural Networks

    ORAL

    –

    Presenters

    • Alex Casey

      Mechanical Engineering, Purdue University

    Authors

    • Alex Casey

      Mechanical Engineering, Purdue University

    • Brian Barnes

      Army Research Laboratory, Detonation Science and Modeling Branch, CCDC Army Research Laboratory, CCDC Army Research Laboratory, US Army Rsch Lab - Aberdeen

    • Ilias Bilionis

      Mechanical Engineering, Purdue University

    • Steven F. Son

      Mechanical Engineering, Purdue University, Purdue University

    View abstract →

  • Optimization of Molecular Characteristic using Continuous Representation of Molecules by Variational Autoencoder with Discriminator

    ORAL

    –

    Presenters

    • Kyosuke Sato

      Graduate School of Natural Science and Technology, Okayama University, Okayama Univ

    Authors

    • Kyosuke Sato

      Graduate School of Natural Science and Technology, Okayama University, Okayama Univ

    • Kenji Tsuruta

      Graduate School of Natural Science and Technology, Okayama University, Okayama Univ

    View abstract →

  • An Initial Design-based Deep Learning Procedure for the Optimization of High Dimensional ReaxFF Parameters

    ORAL

    –

    Presenters

    • Mert Yigit Sengul

      Materials Science and Engineering, The Pennsylvania State University, Pennsylvania State University

    Authors

    • Mert Yigit Sengul

      Materials Science and Engineering, The Pennsylvania State University, Pennsylvania State University

    • Yao Song

      Department of Statistics, Rutgers University

    • Linglin He

      Department of Statistics, Rutgers University

    • Ying Hung

      Department of Statistics, Rutgers University

    • Tirthankar Dasgupta

      Department of Statistics, Rutgers University

    • Adri C.T. van Duin

      Department of Mechanical Engineering, Penn State University, Pennsylvania State University, Mechanical Engineering, Pennsylvania State University

    View abstract →

  • Feature Extraction Using Semi-Supervised Deep Learning.

    ORAL

    –

    Presenters

    • Muammar El Khatib

      Computational Research Division, Lawrence Berkeley National Laboratory

    Authors

    • Muammar El Khatib

      Computational Research Division, Lawrence Berkeley National Laboratory

    • Wibe A De Jong

      Computational Research Division, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Computational Chemistry, Materials and Climate Group, Lawrence Berkeley National Laboratory

    View abstract →

  • Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

    ORAL

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    Presenters

    • Samuel Kim

      Electrical Engineering and Computer Science, Massachusetts Institute of Technology

    Authors

    • Samuel Kim

      Electrical Engineering and Computer Science, Massachusetts Institute of Technology

    • Peter Lu

      Physics, Massachusetts Institute of Technology, Department of Physics, Massachusetts Institute of Technology

    • Michael Gilbert

      Electrical Engineering and Computer Science, Massachusetts Institute of Technology

    • Srijon Mukherjee

      Physics, Massachusetts Institute of Technology

    • Li Jing

      Physics, Massachusetts Institute of Technology

    • Vladimir Čeperić

      University of Zagreb

    • Marin Soljacic

      Physics, Massachusetts Institute of Technology, Department of Physics, Massachusetts Institute of Technology

    View abstract →

  • Turbulence-generating networks

    ORAL

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    Presenters

    • Armando Garcia

      University of Texas, El Paso

    Authors

    • Armando Garcia

      University of Texas, El Paso

    • Rao Gudimetla

      Air Force Research Laboratory, Air Force Research Lab

    • Jorge Munoz

      University of Texas, El Paso

    View abstract →