Alexie M. Kolpak

发表

Accelerating atomistic modelling with active learning

Jonathan Vandermause, Steven Torrisi, Simon Batzner, 2019 .

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

Alexie M. Kolpak, Brian Kolb, Levi C. Lentz, 2017, Scientific Reports.

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Jonathan Vandermause, Simon Batzner, Alexie M. Kolpak, 2020, npj Computational Materials.

Catalytic behavior at the nanoscale: CO adsorption on Al2O3-supported Pt clusters

Alexie M. Kolpak, Andrew M. Rappe, Valentino R. Cooper, 2003, SPIE Optics + Photonics.

Automated training of machine learned potentials with Bayesian active learning

Jonathan Vandermause, Simon Batzner, Alexie M. Kolpak, 2020 .

Elucidating the Nature of the Active Phase in Copper/Ceria Catalysts for CO Oxidation

Yang Shao-Horn, Alexie M. Kolpak, Nongnuch Artrith, 2016 .

Grand canonical molecular dynamics simulations of Cu–Au nanoalloys in thermal equilibrium using reactive ANN potentials

Alexie M. Kolpak, Nongnuch Artrith, Nongnuch Artrith, 2015 .

On-the-Fly Bayesian Active Learning of Interpretable Force-Fields for Atomistic Rare Events

Jonathan Vandermause, Simon Batzner, Alexie M. Kolpak, 2019 .

Ferroelectricity in ultrathin perovskite films

Alexie M. Kolpak, Na Sai, Andrew M. Rappe, 2005 .