ENTITY
AME2016
AME2016
PulseAugur coverage of AME2016 — every cluster mentioning AME2016 across labs, papers, and developer communities, ranked by signal.
Total · 30d
0
2 over 90d
Releases · 30d
0
0 over 90d
Papers · 30d
0
2 over 90d
TIER MIX · 90D
TOPICS
RECENT · PAGE 1/1 · 2 TOTAL
-
Interpretable Neural Networks Leverage Nuclear Symmetries for Mass Prediction
Researchers have developed three novel neural network models—FINN, GINN, and WINN—to explore nuclear symmetries and predict nuclear masses. These models, trained on AME2016 and validated against AME2020 data, demonstrat…
-
New GRU model enhances nuclear mass prediction accuracy
Researchers have developed a new machine learning technique using gated recurrent units (GRUs) to improve the prediction of atomic nuclei masses. By incorporating multiplicative interactions and product-unit transformat…