30 citations · 37 across the 3 of their papers we have counts for
3 papers
Scalable Training of Neural Network Potentials for Complex Interfaces Through Data Augmentation
In Won Yeu, Annika Stuke, Jon L. pez-Zorrilla +5
Artificial neural network (ANN) potentials enable highly accurate atomistic simulations of complex materials at unprecedented scales. Despite their promise, training ANN potentials…
ænet-PyTorch: a GPU-supported implementation for machine learning atomic potentials training
Jon Lopez-Zorrilla, Xabier M. Aretxabaleta, Inwon Yue +3
In this work, we present ænet-PyTorch, a PyTorch-based implementation for training artificial neural network-based machine learning interatomic potentials. Developed as an extensio…
InterPhon: Ab initio Interface Phonon Calculations within a 3D Electronic Structure Framework
In Won Yeu, Gyuseung Han, Kun Hee Ye +2
This work provides the community with an easily executable open-source Python package designed to automize the evaluation of Interfacial Phonons (InterPhon). Its strategy of arbitr…