545 citations · 2.9k across the 55 of their papers we have counts for
5 papers · 1 filter
Machine Learning of consistent thermodynamic models using automatic differentiation
David Rosenberger, Kipton Barros, Timothy C. Germann +1
We propose a data-driven method to describe consistent equations of state (EOS) for arbitrary systems. Complex EOS are traditionally obtained by fitting suitable analytical express…
Machine learning of Kondo physics using variational autoencoders and symbolic regression
Cole Miles, Matthew R. Carbone, Erica J. Sturm +4
We employ variational autoencoders to extract physical insight from a dataset of one-particle Anderson impurity model spectral functions. Autoencoders are trained to find a low-dim…
Quantum-based Molecular Dynamics Simulations Using Tensor Cores
Joshua Finkelstein, Justin S. Smith, Susan M. Mniszewski +4
Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligenc…
Mixed Precision Fermi-Operator Expansion on Tensor Cores From a Machine Learning Perspective
Joshua Finkelstein, Justin Smith, Susan M. Mniszewski +4
We present a second-order recursive Fermi-operator expansion scheme using mixed precision floating point operations to perform electronic structure calculations using tensor core u…
Quantum Monte Carlo study of an anharmonic Holstein model
G. Paleari, F. Hébert, B. Cohen-Stead +3
We study the effects of anharmonicity on the physics of the Holstein model, which describes the coupling of itinerant fermions and localized quantum phonons, by introducing a quart…