How can we use ML in Nuclear Science?
- How do we develop insights, competences, knowledge in statistical learning that can advance our field?
- For example: Can we use ML to find out which correlations are relevant and thereby diminish the dimensionality problem in standard many-body theories?
- Can we use AI/ML in detector analysis, accelerator design, analysis of experimental data and more?
- Can we use AL/ML to carry out reliable extrapolations by using current experimental knowledge and current theoretical models?
- Future research may have a strong focus on generative models
- The community needs to invest in relevant educational efforts and training of nuclear physicists with knowledge in AI/ML
- Most likely tons of things we have forgotten