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- Argonne National LaboratoryUS75 papers
- Boston UniversityUS15 papers
- Lawrence Livermore National LaboratoryUS13 papers
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- University of BaselCH10 papers
- University of Colorado BoulderUS10 papers
- Brookhaven National LaboratoryUS9 papers
- Los Alamos National LaboratoryUS9 papers
- University of California, DavisUS9 papers
- University of ChicagoUS9 papers
- Lawrence Berkeley National LaboratoryUS8 papers
- Syracuse UniversityUS7 papers
8 papers · 1 filter
Deep Learning Models for Global Coordinate Transformations that Linearize PDEs
Craig Gin, Bethany Lusch, Steven L. Brunton +1
We develop a deep autoencoder architecture that can be used to find a coordinate transformation which turns a nonlinear PDE into a linear PDE. Our architecture is motivated by the…
Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur +5
We propose a novel active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our act…
A turbulent eddy-viscosity surrogate modeling framework for Reynolds-Averaged Navier-Stokes simulations
Romit Maulik, Himanshu Sharma, Saumil Patel +2
The Reynolds-averaged Navier-Stokes (RANS) equations for steady-state assessment of incompressible turbulent flows remain the workhorse for practical computational fluid dynamics (…
Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting
Tanwi Mallick, Prasanna Balaprakash, Eric Rask +1
Traffic forecasting approaches are critical to developing adaptive strategies for mobility. Traffic patterns have complex spatial and temporal dependencies that make accurate forec…
Time-series learning of latent-space dynamics for reduced-order model closure
Romit Maulik, Arvind Mohan, Bethany Lusch +3
We study the performance of long short-term memory networks (LSTMs) and neural ordinary differential equations (NODEs) in learning latent-space representations of dynamical equatio…
Defect energetics of cubic hafnia from quantum Monte Carlo simulations
Raghuveer Chimata, Hyeondeok Shin, Anouar Benali +1
Cubic hafnia (HfO) is of great interest for a number of applications in electronics because of its high dielectric constant. However, common defects in such applications degrad…