1 citations · 1 across the 2 of their papers we have counts for
4 papers
Advancing Nuclear Physics with Machine Learning and Artificial Intelligence
Wanbing He, Qingfeng Li, Yugang Ma +3
Machine learning (ML) and artificial intelligence (AI) are becoming powerful tools in scientific research across various disciplines. In this review, we summarize recent progress i…
Nuclear mass prediction using bidirectional recurrent neural networks with isotopic and isotonic chain correlations
P. Li, Y. F. Niu, F. Q. Chen +1
Nuclear masses are fundamental quantities in nuclear physics, providing essential information for understanding nuclear structure, decay properties, and reaction processes. Here we…
Stellar -decay rate of Ni and its impact on the -process nucleosynthesis in massive stars
Xin-Xu Wang, Bao-Hua Sun, Toshitaka Kajino +4
The -decay rate of Ni, an important branching point, affects the subsequent nucleosynthesis in the weak component of the slow-neutron capture process (weak -proces…
Machine learning in nuclear physics at low and intermediate energies
Wanbing He, Qingfeng Li, Yugang Ma +3
Machine learning is becoming a new paradigm for scientific research in various research fields due to its exciting and powerful capability of modeling tools used for big-data proce…