Publication
D. Willimetz
L. Grajciar
A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning
A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning
The Journal of Physical Chemistry Letters,
16(42),
2025
Reference
@article{Willimetz_2025,
author = "D. Willimetz and L. Grajciar",
title = "A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning",
year = 2025,
journal = "The Journal of Physical Chemistry Letters",
publisher = "American Chemical Society (ACS)",
volume = 16,
number = 42,
month = "Oct",
doi = "10.1021/acs.jpclett.5c02595",
url = "http://dx.doi.org/10.1021/acs.jpclett.5c02595"
}