Machine Learning

Presentations

• Towards learning a Lattice Boltzmann collisional operator

  ORAL

  March 9, 2023, 8:00 AM – March 9, 2023, 8:12 AM

  Presenters

  • Alessandro Gabbana

    • Eindhoven University of Technology

  Authors

  • Alessandro Gabbana

    • Eindhoven University of Technology

  • Alessandro Corbetta

    • Eindhoven University of Technology

  • Vitaliy Gyrya

    • Los Alamos National Laboratory

  • Daniel Livescu

    • LANL

  • Joost Prins

    • Eindhoven University of Technology

  • Federico Toschi

    • Eindhoven University of Technology

  View abstract →

• Learning closure models with neural operator-embedded differentiable CFD

  ORAL

  March 9, 2023, 8:12 AM – March 9, 2023, 8:24 AM

  Presenters

  • Varun Shankar

    • Carnegie Mellon University

  Authors

  • Varun Shankar

    • Carnegie Mellon University

  • Venkat Viswanathan

    • Carnegie Mellon University

  View abstract →

• A data-free partial differential equation (PDE) solver in the framework of physics-informed neural networks (PINN)

  ORAL

  March 9, 2023, 8:24 AM – March 9, 2023, 8:36 AM

  Presenters

  • Boqian Yan

    • Northeastern University

  Authors

  • Xiaoyu Tang

    • Northeastern University

  • Boqian Yan

    • Northeastern University

  View abstract →

• Defending smart electrical power grids against cyberattacks with deep Q-learning

  ORAL

  March 9, 2023, 8:36 AM – March 9, 2023, 8:48 AM

  Publication: Defending smart electrical power grids against cyberattacks with deep Q-learning
  PRX Energy
  Mohammadamin Moradi, Yang Weng, and Ying-Cheng Lai
  Accepted10 October 2022

  Presenters

  • Mohammadamin Moradi

    • Arizona State University

  Authors

  • Mohammadamin Moradi

    • Arizona State University

  • Ying-Cheng Lai

    • Arizona State University

  • Yang Weng

    • Arizona State University

  View abstract →

• Using transfer learning to generate samples for large systems of the spin-fermion Hamiltonian

  ORAL

  March 9, 2023, 8:48 AM – March 9, 2023, 9:00 AM

  Presenters

  • Georgios Stratis

    • Northeastern University

  Authors

  • Georgios Stratis

    • Northeastern University

  • Pau Closas

    • Northeastern University

  • Adrian E Feiguin

    • Northeastern University

  View abstract →

• Learning Coronal Nonlinear Force-Free Magnetic Fields through Differentiable Rendering

  ORAL

  March 9, 2023, 9:00 AM – March 9, 2023, 9:12 AM

  Publication: Planned paper: Learning Coronal Nonlinear Force-Free Magnetic Fields through Differentiable Rendering

  Presenters

  • Phillip Lo

    • University of Chicago

  Authors

  • Phillip Lo

    • University of Chicago

  • Eric Jonas

    • University of Chicago

  View abstract →

• Multiscale Perturbed Gradient Descent: Chaotic Regularization and Heavy-Tailed Limits

  ORAL

  March 9, 2023, 9:12 AM – March 9, 2023, 9:24 AM

  Publication: https://arxiv.org/abs/2205.11361

  Presenters

  • Soon Hoe Lim

    • NORDITA

  Authors

  • Soon Hoe Lim

    • NORDITA

  View abstract →

• Data-driven discovery and interpolation of Green's functions

  ORAL

  March 9, 2023, 9:24 AM – March 9, 2023, 9:36 AM

  Presenters

  • Harshwardhan Praveen

    • Cornell University

  Authors

  • Harshwardhan Praveen

    • Cornell University

  • Nicolas Boulle

    • University of Cambridge

  • Christopher J Earls

    • Cornell University

  View abstract →

• Toward automated design of optimized high energy density material science experiments on the Z Machine

  ORAL

  March 9, 2023, 9:36 AM – March 9, 2023, 9:48 AM

  Presenters

  • Andrew J Porwitzky

    • Sandia National Laboratories

  Authors

  • Andrew J Porwitzky

    • Sandia National Laboratories

  • Justin L Brown

    • Sandia National Laboratories

  • William E Lewis

    • Sandia National Laboratories

  View abstract →

• Using deep-learning to uncover physics of magnetic (charged particle) confinement in Magnetized Liner Inertial Fusion

  ORAL

  March 9, 2023, 9:48 AM – March 9, 2023, 10:00 AM

  Publication: Deep-learning-enabled Bayesian inference of fuel magnetization in magnetized liner inertial fusion (editors-pick)
  W.E. Lewis et al. Physics of Plasmas 28, 092701 (2021)
  https://doi.org/10.1063/5.0056749

  Presenters

  • William E Lewis

    • Sandia National Laboratories

  Authors

  • William E Lewis

    • Sandia National Laboratories

  • Owen M Mannion

    • Sandia National Laboratories

  • Christopher A Jennings

    • Sandia National Laboratories

  • Daniel E Ruiz

    • Sandia National Laboratories

  • Patrick F Knapp

    • Sandia National Laboratories

  • Matthew R Gomez

    • Sandia National Laboratories

  • Adam J Harvey-Thompson

    • Sandia National Laboratories

  • Stephen A Slutz

    • Sandia National Laboratories

  • Kristian Beckwith

    • Sandia National Laboratories

  • Kristian Beckwith

    • Sandia National Laboratories

  View abstract →

• MADEM: Energy-efficient training of Deep neural networks using Memristor arrays

  ORAL

  March 9, 2023, 10:00 AM – March 9, 2023, 10:12 AM

  Publication: S.Yi, J.Kendall, R.S.Williams, S.Kumar, "MADEM: Activity-Difference Training of Deep Neural Networks using Memristors" Nature Electronics [Accepted on Aug. 30th]

  Presenters

  • Suin Yi

    • Texas A&M University

  Authors

  • Suin Yi

    • Texas A&M University

  • Suhas Kumar

    • Stanford University
    • Sandia National Laboratories
    • Sandia National Laboratories, CA
    • Sandia National Labs

  View abstract →

• Automatic detection of fake tweets about Covid-19 Vaccine in Portuguese

  ORAL

  March 9, 2023, 10:12 AM – March 9, 2023, 10:24 AM

  Presenters

  • Rafael Geurgas Zavarizz

    • unicamp

  Authors

  • Rafael Geurgas Zavarizz

    • unicamp

  • Leandro R Tessler

    • unicamp

  View abstract →

• Transferable Coarse Grained Free Energy Models Enabled by Active Learning

  ORAL

  March 9, 2023, 10:24 AM – March 9, 2023, 10:36 AM

  Presenters

  • Blake R Duschatko

    • Harvard University

  Authors

  • Blake R Duschatko

    • Harvard University

  • Jonathan P Vandermause

    • Harvard University

  • Nicola Molinari

    • Harvard University

  • Boris Kozinsky

    • Harvard University

  View abstract →