22 citations · 40 across the 2 of their papers we have counts for
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cond-mat.str-el2021★ 18 cited
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…
cond-mat.str-el2020★ 22 cited
Predicting impurity spectral functions using machine learning
Erica J. Sturm, Matthew R. Carbone, Deyu Lu +2
The Anderson Impurity Model (AIM) is a canonical model of quantum many-body physics. Here we investigate whether machine learning models, both neural networks (NN) and kernel ridge…