Designing Neural Networks for the Structure of Physics Data

Presentations

• Unified Graph Neural Network Force-field for the Periodic Table

  ORAL · Invited

  March 7, 2023, 3:00 PM – March 7, 2023, 3:36 PM

  Presenters

  • Kamal Choudhary

    • National Institute of Standards and Tech

  Authors

  • Kamal Choudhary

    • National Institute of Standards and Tech

  View abstract →

• Structure-motif-based material network for functional material discovery.

  ORAL

  March 7, 2023, 3:36 PM – March 7, 2023, 3:48 PM

  Presenters

  • Anoj Aryal

    • Northeastern University

  Authors

  • Anoj Aryal

    • Northeastern University

  • Huta Banjade

    • Virginia Commonwealth University

  • Qimin Yan

    • Northeastern University

  View abstract →

• Physically informed graph neural networks for prediction of optical properties of solid materials

  ORAL

  March 7, 2023, 3:48 PM – March 7, 2023, 4:00 PM

  Presenters

  • Can Ataca

    • University of Maryland, Baltimore County

  Authors

  • Can Ataca

    • University of Maryland, Baltimore County

  • Akram Ibrahim

    • University of Maryland Baltimore County

  View abstract →

• Mario Geiger

  ORAL · Invited

  March 7, 2023, 4:00 PM – March 7, 2023, 4:36 PM

  Presenters

  • Mario Geiger

    • MIT
    • Swiss Federal Institute of Technology Lausanne (EPFL )

  Authors

  • Mario Geiger

    • MIT
    • Swiss Federal Institute of Technology Lausanne (EPFL )

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• Understanding Self-Assembly Behavior with Self-Supervised Learning

  ORAL

  March 7, 2023, 4:36 PM – March 7, 2023, 4:48 PM

  Publication: https://arxiv.org/abs/2110.02393 ; also a more tailored preprint that is under review as of submission

  Presenters

  • Matthew Spellings

    • Vector Institute for Artificial Intelligence

  Authors

  • Matthew Spellings

    • Vector Institute for Artificial Intelligence

  • Maya Martirossyan

    • Cornell University

  • Julia Dshemuchadse

    • Cornell University

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• Metric geometry tools for automatic structure phase map generation

  ORAL

  March 7, 2023, 4:48 PM – March 7, 2023, 5:00 PM

  Presenters

  • Kiran Vaddi

    • University of Washington

  Authors

  • Kiran Vaddi

    • University of Washington

  • Karen Li

    • University of Washington

  • Lilo Pozzo

    • University of Washington

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• Graph neural network accelerated generalizable stress field prediction for mesh-based finite element simulations

  ORAL

  March 7, 2023, 5:00 PM – March 7, 2023, 5:12 PM

  Presenters

  • Bowen Zheng

    • University of California at Berkeley
    • University of California, Berkeley

  Authors

  • Bowen Zheng

    • University of California at Berkeley
    • University of California, Berkeley

  • Zeqing Jin

    • University of California, Berkeley

  • Changgon Kim

    • Hyundai Motor Company

  • Grace X Gu

    • University of California at Berkeley
    • University of California, Berkeley

  View abstract →

• Modeling the Band Structure of Periodic Crystals with Physics-Informed Neural Networks

  ORAL

  March 7, 2023, 5:12 PM – March 7, 2023, 5:24 PM

  Presenters

  • Circe Hsu

    • Northeastern University

  Authors

  • Circe Hsu

    • Northeastern University

  • Daniel T Larson

    • Harvard University
    • Department of Physics, Harvard University

  • Gabriel R Schleder

    • Harvard University

  • Marios Mattheakis

    • Harvard University

  • Efthimios Kaxiras

    • Harvard University

  View abstract →

• Using CycleGANs to construct training data for other Machine Learning models

  ORAL

  March 7, 2023, 5:24 PM – March 7, 2023, 5:36 PM

  Presenters

  • Abid A Khan

    • University of Illinois at Urbana-Champai

  Authors

  • Abid A Khan

    • University of Illinois at Urbana-Champai

  • Chia-Hao Lee

    • University of Illinois at Urbana-Champaign

  • Pinshane Y Huang

    • University of Illinois at Urbana-Champaign

  • Bryan K Clark

    • University of Illinois at Urbana-Champaign

  View abstract →

• Contrastive Learning Reveals the Trajectory of Protein Structure Evolution

  ORAL

  March 7, 2023, 5:36 PM – March 7, 2023, 5:48 PM

  Presenters

  • Yong Wei

    • High Point University

  Authors

  • Yong Wei

    • High Point University

  • Baofu Qiao

    • City University of New York

  • Tao Wei

    • Howard University

  • Hanning Chen

    • The University of Texas at Austin

  View abstract →

• Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics

  ORAL

  March 7, 2023, 5:48 PM – March 7, 2023, 6:00 PM

  Publication: Title: GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions. Authors: Ryan Lopez and Paul J. Atzberger. (Submitted to JMLR, arxiv link: https://arxiv.org/pdf/2206.05183.pdf)

  Presenters

  • Ryan Lopez

    • Massachusetts Institute of Technology

  Authors

  • Ryan Lopez

    • Massachusetts Institute of Technology

  • Paul J Atzberger

    • University of California, Santa Barbara

  View abstract →