research
∙
07/16/2021
Machine-learning Kondo physics using variational autoencoders
We employ variational autoencoders to extract physical insight from a da...
share
research
∙
06/09/2020
Simple and efficient algorithms for training machine learning potentials to force data
Abstract Machine learning models, trained on data from ab initio quantum...
research
∙
03/10/2020
Automated discovery of a robust interatomic potential for aluminum
Atomistic molecular dynamics simulation is an important tool for predict...
research
∙
09/29/2017
Hierarchical modeling of molecular energies using a deep neural network
We introduce the Hierarchically Interacting Particle Neural Network (HIP...
research
∙
11/08/2016