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

  View abstract →

• 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 →