Machine learning the deuteron: new architectures and uncertainty quantification (2022)
Attributed to:
Advancing Nuclear Science via Theory and Experiment
funded by
STFC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.48550/arxiv.2205.12795
Publication URI: https://arxiv.org/abs/2205.12795
Type: Preprint