Machine Learning in Nonlinear Physics and Mechanics

Presentations

• A unified perspective on disorder in atomic systems: machine learning material properties and design

  Invited

  March 6, 2018, 11:15 AM – March 6, 2018, 11:51 AM

  Presenters

  • Ekin Cubuk

    • Stanford University
    • Google Brain
    • Stanford Univ

  Authors

  • Ekin Cubuk

    • Stanford University
    • Google Brain
    • Stanford Univ

  View abstract →

• Predicting the dynamics of crumpling with machine learning

  ORAL

  March 6, 2018, 11:51 AM – March 6, 2018, 12:03 PM

  Presenters

  • Christopher Rycroft

    • SEAS, Harvard Univ
    • Harvard University
    • SEAS, Harvard University
    • John A. Paulson School of Engineering and Applied Sciences, Harvard University
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Mathematics, Harvard University

  Authors

  • Christopher Rycroft

    • SEAS, Harvard Univ
    • Harvard University
    • SEAS, Harvard University
    • John A. Paulson School of Engineering and Applied Sciences, Harvard University
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Mathematics, Harvard University

  • Jordan Hoffmann

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Jovana Andrejevic

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Lisa Lee

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Shmuel Rubinstein

    • SEAS, John A Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Physics, Harvard Univ
    • SEAS, Harvard Univ
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • SEAS, Harvard University
    • Harvard University

  View abstract →

• Detection and Characterization Techniques for Signatures of Crumpling History

  ORAL

  March 6, 2018, 12:03 PM – March 6, 2018, 12:15 PM

  Presenters

  • Jovana Andrejevic

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  Authors

  • Jovana Andrejevic

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Jordan Hoffmann

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Lisa Lee

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Shmuel Rubinstein

    • SEAS, John A Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Physics, Harvard Univ
    • SEAS, Harvard Univ
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • SEAS, Harvard University
    • Harvard University

  • Christopher Rycroft

    • SEAS, Harvard Univ
    • Harvard University
    • SEAS, Harvard University
    • John A. Paulson School of Engineering and Applied Sciences, Harvard University
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Mathematics, Harvard University

  View abstract →

• Using Machine Learning to Understand the Evolution of Damage Networks in Thin Sheets

  ORAL

  March 6, 2018, 12:15 PM – March 6, 2018, 12:27 PM

  Presenters

  • Lisa Lee

    • Harvard Univ

  Authors

  • Lisa Lee

    • Harvard Univ

  • Jovana Andrejevic

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Jordan Hoffmann

    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University

  • Christopher Rycroft

    • SEAS, Harvard Univ
    • Harvard University
    • SEAS, Harvard University
    • John A. Paulson School of Engineering and Applied Sciences, Harvard University
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Mathematics, Harvard University

  • Shmuel Rubinstein

    • SEAS, John A Paulson School of Engineering and Applied Sciences, Harvard University
    • Applied Physics, Harvard Univ
    • SEAS, Harvard Univ
    • Harvard Univ
    • Paulson School of Engineering and Applied Sciences, Harvard University
    • SEAS, Harvard University
    • Harvard University

  View abstract →

• Identifying Structural Defects in Disordered Packings of Elongated Particles using Machine Learning

  ORAL

  March 6, 2018, 12:27 PM – March 6, 2018, 12:39 PM

  Presenters

  • Matt Harrington

    • University of Pennsylvania

  Authors

  • Matt Harrington

    • University of Pennsylvania

  • Andrea Liu

    • University of Pennsylvania
    • Univ of Pennsylvania
    • Department of Physics and Astronomy, Department of Physics and Astronomy
    • Department of Physics and Astronomy, University of Pennsylvania

  • Douglas Durian

    • Department of Physics & Astronomy, University of Pennsylvania
    • Department of Physics and Astronomy, Univ of Pennsylvania
    • University of Pennsylvania

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• Reservoir computer predictions for the Three Meter magnetic field time evolution

  ORAL

  March 6, 2018, 12:39 PM – March 6, 2018, 12:51 PM

  Presenters

  • Artur Perevalov

    • Physics, IREAP, University of Maryland College Park

  Authors

  • Artur Perevalov

    • Physics, IREAP, University of Maryland College Park

  • Ruben Rojas Garcia

    • Physics, IREAP, University of Maryland College Park

  • Itamar Shani

    • Physics, IREAP, University of Maryland College Park

  • Brian Hunt

    • Institute for Physical Sciences and Technology, University of Maryland College Park

  • Daniel Lathrop

    • Physics, University of Maryland
    • Physics, IREAP, University of Maryland College Park

  View abstract →

• Using image Super-Resolution techniques as a coarse-graining method for physical systems

  ORAL

  March 6, 2018, 12:51 PM – March 6, 2018, 1:03 PM

  Presenters

  • Yohai Bar-Sinai

    • SEAS, Harvard University
    • Harvard Univ

  Authors

  • Yohai Bar-Sinai

    • SEAS, Harvard University
    • Harvard Univ

  • Michael Brenner

    • Harvard University
    • School of Engineering and Applied Sciences, Harvard University
    • SEAS, Harvard University

  • Pascal Getreuer

    • Google Research, Google

  • Jason Hickey

    • Google Research, Google

  • Stephan Hoyer

    • Google Research, Google

  • Peyman Milanfar

    • Google Research, Google

  View abstract →

• Predicting Emergent Crystalline Structural Order from Building Block Geometry

  ORAL

  March 6, 2018, 1:03 PM – March 6, 2018, 1:15 PM

  Presenters

  • Yina Geng

    • Univ of Michigan - Ann Arbor

  Authors

  • Yina Geng

    • Univ of Michigan - Ann Arbor

  • Greg Van Anders

    • Department of Physics, University of Michigan
    • Univ of Michigan - Ann Arbor
    • Department of Physics, Univ of Michigan - Ann Arbor
    • University Michigan

  • Sharon Glotzer

    • Chemical Engineering, Univ of Michigan - Ann Arbor
    • Univ of Michigan - Ann Arbor
    • Department of Chemical Engineering, University of Michigan - Ann Arbor
    • Department of Chemical Engineering, University of Michigan
    • Chemical Engineering, University of Michigan
    • Department of Chemical Engineering, Univ of Michigan - Ann Arbor

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• Intelligent, autonomous parameter space exploration of self-assembly simulations

  ORAL

  March 6, 2018, 1:15 PM – March 6, 2018, 1:27 PM

  Presenters

  • Matthew Spellings

    • Chemical Engineering, University of Michigan

  Authors

  • Matthew Spellings

    • Chemical Engineering, University of Michigan

  • Julia Dshemuchadse

    • Chemical Engineering, University of Michigan

  • Sharon Glotzer

    • Chemical Engineering, Univ of Michigan - Ann Arbor
    • Univ of Michigan - Ann Arbor
    • Department of Chemical Engineering, University of Michigan - Ann Arbor
    • Department of Chemical Engineering, University of Michigan
    • Chemical Engineering, University of Michigan
    • Department of Chemical Engineering, Univ of Michigan - Ann Arbor

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• Distilling the logic of behavioral dynamics using automated inference

  ORAL

  March 6, 2018, 1:27 PM – March 6, 2018, 1:39 PM

  Presenters

  • Bryan Daniels

    • ASU–SFI Center for Biosocial Complex Systems, Arizona State University

  Authors

  • Bryan Daniels

    • ASU–SFI Center for Biosocial Complex Systems, Arizona State University

  • William Ryu

    • University of Toronto

  • Ilya Nemenman

    • Emory Univ
    • Emory University
    • Department of Physics, Department of Biology, Emory University

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• Computational tools for data-driven design of soft robots

  ORAL

  March 6, 2018, 1:39 PM – March 6, 2018, 1:51 PM

  Presenters

  • Mohammad Khalid Jawed

    • University of California, Los Angeles
    • Department of Mechanical and Aerospace Engineering, Univ of California - Los Angeles

  Authors

  • Mohammad Khalid Jawed

    • University of California, Los Angeles
    • Department of Mechanical and Aerospace Engineering, Univ of California - Los Angeles

  • Xiaonan Huang

    • Mechanical Engineering, Carnegie Mellon University
    • Department of Mechanical Engineering, Carnegie Mellon University

  • Amarbold Batzorig

    • California Institute of Technology
    • Department of Mechanical Engineering, Carnegie Mellon University

  • Carmel Majidi

    • Mechanical Engineering, Carnegie Mellon University
    • Department of Mechanical Engineering, Carnegie Mellon University

  View abstract →

• Deep Learning Physical Phenomena

  ORAL

  March 6, 2018, 1:51 PM – March 6, 2018, 2:03 PM

  Presenters

  • Joseph Gomes

    • Chemistry, Stanford University

  Authors

  • Joseph Gomes

    • Chemistry, Stanford University

  • Amir Barati Farimani

    • Univ of Illinois - Urbana
    • Chemistry, Stanford University

  • Vijay Pande

    • Chemistry, Stanford University

  View abstract →

• Visualizing theory space: Isometric embedding of probabilistic predictions, from the Ising model to the cosmic microwave background

  ORAL

  March 6, 2018, 2:03 PM – March 6, 2018, 2:15 PM

  Presenters

  • Katherine Quinn

    • Physics, Cornell University

  Authors

  • Katherine Quinn

    • Physics, Cornell University

  • Francesco De Bernardis

    • Physics, Cornell University

  • Michael Niemack

    • Physics, Cornell University

  • James Sethna

    • Cornell University
    • Laboratory of Atomic and Solid State Physics, Cornell University
    • Physics, Cornell University

  View abstract →