Nov 26 – 27, 2020
RIKEN Wako Campus
Asia/Tokyo timezone

Nuclear data generation using machine learning

Not scheduled
RIBF201 (RIKEN Wako Campus)


RIKEN Wako Campus

Hirosawa 2-1, Wako City, Saitama 351-0198, Japan
Oral Presentation DeepLearning


Hiroki Iwamoto (Japan Atomic Energy Agency)


We have developed a method to generate nuclear data using Gaussian process regression (GPR) [1], which is one of the machine learning techniques. This method generates nuclear data by treating measured data as the training data in machine learning. GPR is based on nonparametric Bayesian inference, the generated nuclear data are expressed as a predictive distribution including uncertainty information. In this presentation, the basics of the Gaussian process model, some examples of the application to nuclear data generation, and other related topics will be presented.

[1] H. Iwamoto, “Generation of nuclear data using Gaussian process regression”, Journal of Nuclear Science and Technology, 50:8, 932-938 (2020).

Primary author

Hiroki Iwamoto (Japan Atomic Energy Agency)

Presentation materials

Peer reviewing


Paper files: