Symposium on Nuclear Data 2020

Session

DeepLearning

27 Nov 2020, 13:30

RIBF201 (RIKEN Wako Campus)

Conveners

DeepLearning

• Hiroyuki Koura

11. Deep Learning for Basic Science

Masato Taki (Rikkyo University)

27/11/2020, 13:30

Deep Learning for Basic Science

13. Data-driven approaches for nuclear shell-model calculations

Noritaka Shimizu (Center for Nuclear Study, University of Tokyo)

27/11/2020, 14:00

Data-driven approaches for nuclear shell-model calculations

12. Nuclear data generation using machine learning

Hiroki Iwamoto (JAEA)

27/11/2020, 14:30

Nuclear data generation using machine learning

14. Exploration of automated data processing for mass production of nuclear data at RIBF

Shoichiro Kawase (Kyushu University)

27/11/2020, 15:00

Exploration of automated data processing for mass production of nuclear data at RIBF

25. Nuclear data generation using machine learning

Hiroki Iwamoto (Japan Atomic Energy Agency)

Oral Presentation

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...