AI/ML
· 10 papers, 17 presentations · all tags
Papers filter the publication list
- NuGNN: a Graph Neural Network for Nuclear Reaction Network Equations
- Constraining nuclear mass models using r-process observables with multi-objective optimization
- Emulation of the final r-process abundance pattern with a neural network
- Investigating the effects of precise mass measurements of Ru and Pd isotopes on machine learning mass modeling
- Kilonova light-curve interpolation with neural networks
- Uncertainty quantification of mass models using Ensemble Bayesian Model Averaging
- Atomic masses with Machine Learning for the astrophysical r process
- Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach
- Physically Interpretable Machine Learning for nuclear masses
- Nuclear masses learned from a probabilistic neural network
Presentations filter the presentation list
- Machine Learning for global predictions of nuclear excited states
- Nuclear masses at the predictive frontier
- Accelerating mass modeling with scientific machine learning
- Nuclear data in the era of Artificial Intelligence
- Solving inverse problems in nuclear physics with AI/ML
- Machine learning and uncertainty quantification for ground state masses
- Possible limits of elements and isotopes
- Modeling masses with an artificial neural network
- Machine Learning the ground state masses of atomic nuclei
- Modeling masses with an artificial neural network
- Utilizing Machine Learning in low energy nuclear physics
- Nuclear data activities for medium mass and heavy nuclei at Los Alamos
- Ground state masses of nuclei with a probabilistic neural network
- Prediction of nuclear masses with an artificial neural network
- Machine Learning for Nuclear Astrophysics (a first attempt)
- Physically Interpretable Machine Learning for nuclear masses
- Machine Learning and Artificial Intelligence for computational nuclear data