[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)

11/29/22, 1:20 PM

3. Shell model + ML (temporary)

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

11/29/22, 1:30 PM

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

Tsunenori Inakura (Tokyo Tech)

11/29/22, 2:30 PM

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

Dr Haozhao Liang (The University of Tokyo)

11/29/22, 3:40 PM

7. Assessing transfer entropy from biochemical data

Prof. Yoshiyuki Kabashima

11/30/22, 10:00 AM

8. Machine learning assisted density functional theory for electronic systems

Ryosuke Akashi

11/30/22, 11:10 AM

9. Uncertainty evaluation of neutron cross section using T6

Tsunenori Inakura (Tokyo Tech)

11/30/22, 1:00 PM

10. ML for Fission products

Futoshi Minato (Japan Atomic Energy Agency)

11/30/22, 1:40 PM

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

Sota Yoshida (The university of Tokyo)

11/30/22, 2:30 PM

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