[RIBF ULIC MiniWS037] [Rearranged schedule] Combining Nuclear Theory and Machine Learning for fundamental studies and applications

Contribution List

2. opening

Masaaki Kimura (RIKEN Nishina Center)

29/11/2022, 13:20

3. Shell model + ML (temporary)

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

29/11/2022, 13:30

5. Uncertainty evaluation of GDR peak energy and new parameter set

Tsunenori Inakura (Tokyo Tech)

29/11/2022, 14:30

6. Nuclear mass predictions with machine learning reaching the accuracy required by r-process studies

Dr Haozhao Liang (The University of Tokyo)

29/11/2022, 15:40

7. Assessing transfer entropy from biochemical data

Prof. Yoshiyuki Kabashima

30/11/2022, 10:00

8. Machine learning assisted density functional theory for electronic systems

Ryosuke Akashi

30/11/2022, 11:10

9. Uncertainty evaluation of neutron cross section using T6

Tsunenori Inakura (Tokyo Tech)

30/11/2022, 13:00

10. ML for Fission products

Futoshi Minato (Japan Atomic Energy Agency)

30/11/2022, 13:40

11. Learning from what we had disposedandan accelerator to “Machine Learning + nuclear physics”

Sota Yoshida (The university of Tokyo)

30/11/2022, 14:30

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