119 citations · 380 across the 26 of their papers we have counts for
5 papers · 1 filter
Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files
Matthew R. Carbone, Fanchen Meng, Christian Vorwerk +7
First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematical…
The Generalized Green's function Cluster Expansion: A Python package for simulating polarons
Matthew R. Carbone, Stepan Fomichev, Andrew J. Millis +3
We present an efficient implementation of the Generalized Green's function Cluster Expansion (GGCE), which is a new method for computing the ground-state properties and dynamics of…
When not to use machine learning: a perspective on potential and limitations
M. R. Carbone
The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed an enormous amount of research in the scientific community. It has proven to be a po…
Uncertainty-aware predictions of molecular X-ray absorption spectra using neural network ensembles
Animesh Ghose, Mikhail Segal, Fanchen Meng +7
As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important…
Competition between Barrier- and Entropy-Driven Activation in Glasses
Matthew R. Carbone, Marco Baity-Jesi
In simplified models of glasses we clarify the existence of two different kinds of activated dynamics, which coexist, with one of the two dominating over the other. One is the ener…