6 citations · 13 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2021★ 4 cited
Joint machine learning analysis of muon spectroscopy data from different materials
T. Tula, G. Möller, J. Quintanilla +6
Machine learning (ML) methods have proved to be a very successful tool in physical sciences, especially when applied to experimental data analysis. Artificial intelligence is parti…
cond-mat.mtrl-sci2020★ 6 cited
Machine Learning approach to muon spectroscopy analysis
T. Tula, G. Möller, J. Quintanilla +6
In recent years, Artificial Intelligence techniques have proved to be very successful when applied to problems in physical sciences. Here we apply an unsupervised Machine Learning…
cond-mat.dis-nn2020★ 3 cited
Principal Component Analysis of Diffuse Magnetic Scattering: a Theoretical Study
Robert Twyman, Stuart J Gibson, James Molony +1
We present a theoretical study of the potential of Principal Component Analysis to analyse magnetic diffuse neutron scattering data on quantum materials. To address this question,…