Improvement of the Bayesian neural network to study the photoneutron yield cross sections

Precise Machine Learning Models for fragment production in Projectile Fragmentation Reactions by Bayesian Neural Networks

(2022) Chun-Wang 马春旺 Ma et al.   Chinese Physics C

Development of a low-background neutron detector array

(2022) Yu-Tian Li et al.   Nuclear Science and Techniques

Robust restoration of low-dose cerebral perfusion CT images using NCS-Unet

(2022) Kai Chen et al.   Nuclear Science and Techniques

Nuclear mass based on the multi-task learning neural network method

(2022) Xing-Chen Ming et al.   Nuclear Science and Techniques

Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography

(2021) Yin-Jin Ma et al.   Nuclear Science and Techniques

The description of giant dipole resonance key parameters with multitask neural networks

(2021) J.H. Bai et al.   PHYSICS LETTERS B

Hybrid windowed networks for on-the-fly Doppler broadening in RMC code

(2021) Tian-Yi Huang et al.   Nuclear Science and Techniques

Discrimination of neutrons and gamma rays in plastic scintillator based on pulse-coupled neural network

(2021) Hao-Ran Liu et al.   Nuclear Science and Techniques

Yield of long-lived fission product transmutation using proton-, deuteron-, and alpha particle-induced spallation

(2021) Meng-Ting Jin et al.   Nuclear Science and Techniques

Fast nuclide identification based on a sequential Bayesian method

(2021) Xiao-Zhe Li et al.   Nuclear Science and Techniques

Machine learning the nuclear mass

(2021) Ze-Peng Gao et al.   Nuclear Science and Techniques

Isotopic cross-sections in proton induced spallation reactions based on the Bayesian neural network method

(2020) Chun-Wang Ma et al.   Chinese Physics C

IAEA Photonuclear Data Library 2019

(2020) T. Kawano et al.   NUCLEAR DATA SHEETS

Bethe–Weizsäcker semiempirical mass formula coefficients 2019 update based on AME2016

(2020) Djelloul Benzaid et al.   Nuclear Science and Techniques

Giant dipole resonance and shape evolution in Nd isotopes within TDHF method

(2020) Azzeddine Ben Menana et al.   PHYSICA SCRIPTA

Constraining the in-medium nucleon-nucleon cross section from the width of nuclear giant dipole resonance

(2020) Rui Wang et al.   PHYSICS LETTERS B

Constraining symmetry energy at subnormal density by isovector giant dipole resonances of spherical nuclei

(2019) Jun Su   Chinese Physics C

Isoscalar and isovector dipole excitations: Nuclear properties from low-lying states and from the isovector giant dipole resonance

(2019) A. Bracco et al.   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS

Bayesian Evaluation of Incomplete Fission Yields

(2019) Zi-Ao Wang et al.   PHYSICAL REVIEW LETTERS

Giant dipole resonance parameters of ground-state photoabsorption: Experimental values with uncertainties

(2018) V.A. Plujko et al.   ATOMIC DATA AND NUCLEAR DATA TABLES

Nuclear mass predictions based on Bayesian neural network approach with pairing and shell effects

(2018) Z.M. Niu et al.   PHYSICS LETTERS B

Nuclear charge radii: density functional theory meets Bayesian neural networks

(2016) R Utama et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

A study on ground-state energies of nuclei by using neural networks

(2013) Tuncay Bayram et al.   ANNALS OF NUCLEAR ENERGY

Experimental studies of the Pygmy Dipole Resonance

(2013) D. Savran et al.   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS

Decodingβ-decay systematics: A global statistical model forβ−half-lives

(2009) N. J. Costiris et al.   PHYSICAL REVIEW C