6 citations · 16 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.mtrl-sci2017★ 6 cited
Crystal field excitations and magnons: their roles in oxyselenides Pr2O2M2OSe2 (M = Mn, Fe)
R. K. Oogarah, C. P. J. Stockdale, C. Stock +4
We present the results of neutron scattering experiments to study the crystal and magnetic structures of the Mott-insulating transition metal oxyselenides Pr2O2M2OSe2 (M = Mn, Fe).…