Automated discovery of a robust interatomic potential for aluminum

10 March 2020

Papers citing "Automated discovery of a robust interatomic potential for aluminum"

8 / 8 papers shown

Title
Deciphering diffuse scattering with machine learning and the equivariant foundation model: The case of molten FeO Ganesh Sivaraman C. Benmore AI4CE 21 0 0 01 Mar 2024
Spline-based neural network interatomic potentials: blending classical and machine learning models Joshua A Vita D. Trinkle 14 2 0 04 Oct 2023
Accurate melting point prediction through autonomous physics-informed learning O. Klimanova Timofei Miryashkin Alexander Shapeev 4 3 0 23 Jun 2023
Data efficiency and extrapolation trends in neural network interatomic potentials Joshua A Vita Daniel Schwalbe-Koda 42 16 0 12 Feb 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 35 21 0 15 Dec 2022
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties Zeren Shui Daniel S. Karls Mingjian Wen Ilia Nikiforov E. Tadmor George Karypis 46 7 0 14 Oct 2022
Simple and efficient algorithms for training machine learning potentials to force data Justin S. Smith Nicholas Lubbers A. Thompson K. Barros 20 10 0 09 Jun 2020
Modeling nanoconfinement effects using active learning Javier E. Santos M. Mehana Hao Wu M. Prodanović Michael J. Pyrcz Q. Kang Nicholas Lubbers Hari S. Viswanathan AI4CE 9 29 0 06 May 2020