7 citations · 8 across the 13 of their papers we have counts for
4 papers · 1 filter
Teaching Specific Scientific Knowledge into Large Language Models through Additional Training
Kan Hatakeyama-Sato, Yasuhiko Igarashi, Shun Katakami +2
Through additional training, we explore embedding specialized scientific knowledge into the Llama 2 Large Language Model (LLM). Key findings reveal that effective knowledge integra…
Sequential Experimental Design for Spectral Measurement: Active Learning Using a Parametric Model
Tomohiro Nabika, Kenji Nagata, Shun Katakami +2
In this study, we demonstrate a sequential experimental design for spectral measurements by active learning using parametric models as predictors. In spectral measurements, it is n…
Efficient NMR measurement and data analysis supported by the Bayesian inference : The case of the heavy fermion compound YbCo2Zn20
H. Ueda, S. Katakami, S. Yoshida +4
We propose a data-driven technique to infer microscopic physical quantities from nuclear magnetic resonance(NMR) spectra, in which the data size and quality required for the Bayesi…
Bayesian Inference for Small-Angle Scattering Data
Yui Hayashi, Shun Katakami, Shigeo Kuwamoto +3
In this paper, we propose a method for estimating model parameters using Small-Angle Scattering (SAS) data based on the Bayesian inference. Conventional SAS data analyses involve p…