Machine Learning and Data Driven Models I

Presentations

• From Deep to Physics-Informed Learning of Turbulence: Diagnostics

  ORAL

  Nov. 19, 2018, 8:00 AM – Nov. 19, 2018, 8:13 AM

  Presenters

  • Michael Chertkov

    • Los Alamos National Laboratory
    • Los Alamos Natl Lab

  Authors

  • Michael Chertkov

    • Los Alamos National Laboratory
    • Los Alamos Natl Lab

  • Oliver Hennigh

    • Los Alamos National Laboratory

  • Ryan King

    • National Renewable Energy Laboratory

  • Arvind T Mohan

    • Los Alamos National Laboratory

  View abstract →

• Neural Network Powered Adjoint Methods - Gradient Based Shape Optimization with Deep Learning

  ORAL

  Nov. 19, 2018, 8:13 AM – Nov. 19, 2018, 8:26 AM

  Presenters

  • Dana Lynn Ona Lansigan

    • Univ of California - Berkeley

  Authors

  • Dana Lynn Ona Lansigan

    • Univ of California - Berkeley

  • Chiyu Max Jiang

    • Univ of California - Berkeley, UC Berkeley
    • Univ of California - Berkeley, Lawrence Berkeley National Laboratory
    • Univ of California - Berkeley, Lawrence Berkeley National Labratory

  • Philip S Marcus

    • Univ of California - Berkeley
    • University of California, Berkeley

  View abstract →

• Data-driven discretization of PDEs

  ORAL

  Nov. 19, 2018, 8:26 AM – Nov. 19, 2018, 8:39 AM

  Presenters

  • Yohai Bar-Sinai

    • Harvard SEAS

  Authors

  • Yohai Bar-Sinai

    • Harvard SEAS

  • Stephan Hoyer

    • Google

  • Dmitrii Kochkov

    • Google, University of Illinois at Urbana-Champaign

  • Jason Hickey

    • Google

  • Michael Phillip Brenner

    • Harvard SEAS
    • Harvard University
    • Harvard Univ

  View abstract →

• Surrogate Modeling of High-Order Physics-Based Fluid Modeling Tools

  ORAL

  Nov. 19, 2018, 8:39 AM – Nov. 19, 2018, 8:52 AM

  Presenters

  • Robert Zacharias

    • GE Global Research

  Authors

  • Nicholas Magina

    • GE Global Research

  • James Tallman

    • GE Global Research

  • Robert Zacharias

    • GE Global Research

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• Bridging simulation and deep learning - convolutional neural networks on unstructured grids

  ORAL

  Nov. 19, 2018, 8:52 AM – Nov. 19, 2018, 9:05 AM

  Presenters

  • Chiyu Max Jiang

    • Univ of California - Berkeley, UC Berkeley
    • Univ of California - Berkeley, Lawrence Berkeley National Laboratory
    • Univ of California - Berkeley, Lawrence Berkeley National Labratory

  Authors

  • Chiyu Max Jiang

    • Univ of California - Berkeley, UC Berkeley
    • Univ of California - Berkeley, Lawrence Berkeley National Laboratory
    • Univ of California - Berkeley, Lawrence Berkeley National Labratory

  • Karthik Kashinath

    • Lawrence Berkeley National Laboratory

  • Philip S Marcus

    • Univ of California - Berkeley
    • University of California, Berkeley

  • Mr Prabhat

    • Lawrence Berkeley National Laboratory

  View abstract →

• Physics-Informed Generative Learning to Predict Unresolved Physics in Complex Systems

  ORAL

  Nov. 19, 2018, 9:05 AM – Nov. 19, 2018, 9:18 AM

  Presenters

  • Jinlong Wu

    • Virginia Tech

  Authors

  • Jinlong Wu

    • Virginia Tech

  • Yang Zeng

    • Virginia Tech

  • Karthik Kashinath

    • Lawrence Berkeley National Laboratory

  • Adrian Albert

    • Lawrence Berkeley National Laboratory

  • Mr Prabhat

    • Lawrence Berkeley National Laboratory

  • Heng Xiao

    • Virginia Tech

  View abstract →

• A transfer learning approach for data-driven turbulence modeling

  ORAL

  Nov. 19, 2018, 9:18 AM – Nov. 19, 2018, 9:31 AM

  Presenters

  • Rui Fang

    • Harvard University

  Authors

  • Rui Fang

    • Harvard University

  • David Sondak

    • Harvard University

  • Pavlos Protopapas

    • Harvard University

  • Sauro Succi

    • Istituto per le Applicazioni del Calcolo CNR, Rome, Center of Life Nano Science @Sapienza, Istituto Italiano di Tecnologia, Rome
    • IAC/NRC

  View abstract →

• Machine Learning to Improve RANS Turbulent Kinetic Energy Transport Equation

  ORAL

  Nov. 19, 2018, 9:31 AM – Nov. 19, 2018, 9:44 AM

  Presenters

  • David S Ching

    • Stanford University
    • Stanford Univ

  Authors

  • David S Ching

    • Stanford University
    • Stanford Univ

  • Andrew J Banko

    • Stanford University
    • Stanford Univ

  • John Kelly Eaton

    • Stanford University
    • Stanford Univ

  View abstract →

• Physics-Informed Machine Learning Approach for Augmenting Turbulence Models: A Comprehensive Framework

  ORAL

  Nov. 19, 2018, 9:44 AM – Nov. 19, 2018, 9:57 AM

  Presenters

  • Heng Xiao

    • Virginia Tech

  Authors

  • Heng Xiao

    • Virginia Tech

  • Jinlong Wu

    • Virginia Tech

  • Jianxun Wang

    • University of Notre Dame

  • Eric G Paterson

    • Virginia Tech

  View abstract →

• Interpretability of Machine Learning Models for the Reynolds Stress Tensor in Reynolds-Averaged Navier-Stokes Simulations

  ORAL

  Nov. 19, 2018, 9:57 AM – Nov. 19, 2018, 10:10 AM

  Presenters

  • Andrew J Banko

    • Stanford University
    • Stanford Univ

  Authors

  • Andrew J Banko

    • Stanford University
    • Stanford Univ

  • David S Ching

    • Stanford University
    • Stanford Univ

  • Julia Ling

    • Citrine Informatics

  • John Kelly Eaton

    • Stanford University
    • Stanford Univ

  View abstract →