Author

Mohan, Arvind T.

INSPIRE profile2175764 ORCID0000-0002-9434-7691

5 papers

Collaboratorsmost frequent first

	Paper	Category
Sep 25, 2026#72609.29969	Rapid Uncertainty Quantification on a Latent Field using Fisher Information Karl Daningburg · A. E. Lovell🇺🇸 · Arvind T. Mohan · R. O'Shaughnessy🇺🇸	nucl-th	—	0
Apr 19, 2023#22304.08546	Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach M. R. Mumpower🇺🇸 · M. Li · T. M. Sprouse🇺🇸 · B. S. Meyer🇺🇸 · A. E. Lovell🇺🇸 · A. T. Mohan	nucl-th	Front.in Phys.	14
Mar 22, 2022#22203.10594	Physically Interpretable Machine Learning for nuclear masses M. R. Mumpower🇺🇸 · T. M. Sprouse🇺🇸 · A. E. Lovell🇺🇸 · A. T. Mohan	nucl-th	PRC	72
Jan 4, 2022#52201.00676	Nuclear masses learned from a probabilistic neural network A.E. Lovell🇺🇸 · A.T. Mohan · T.M. Sprouse🇺🇸 · M.R. Mumpower🇺🇸	nucl-th	PRC	65
May 8, 2020#32005.03198	Quantifying Uncertainties on Fission Fragment Mass Yields With Mixture Density Networks A.E. Lovell🇺🇸 · A.T. Mohan · P. Talou🇺🇸	nucl-th	J.Phys.G	32

Rapid Uncertainty Quantification on a Latent Field using Fisher Information
Karl Daningburg · A. E. Lovell🇺🇸 · Arvind T. Mohan · R. O'Shaughnessy🇺🇸
Sep 25, 20262609.29969nucl-th0 citations
Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach
M. R. Mumpower🇺🇸 · M. Li · T. M. Sprouse🇺🇸 · B. S. Meyer🇺🇸 · A. E. Lovell🇺🇸 · A. T. Mohan
Apr 19, 20232304.08546nucl-thFront.in Phys.14 citations
Physically Interpretable Machine Learning for nuclear masses
M. R. Mumpower🇺🇸 · T. M. Sprouse🇺🇸 · A. E. Lovell🇺🇸 · A. T. Mohan
Mar 22, 20222203.10594nucl-thPRC72 citations
Nuclear masses learned from a probabilistic neural network
A.E. Lovell🇺🇸 · A.T. Mohan · T.M. Sprouse🇺🇸 · M.R. Mumpower🇺🇸
Jan 4, 20222201.00676nucl-thPRC65 citations
Quantifying Uncertainties on Fission Fragment Mass Yields With Mixture Density Networks
A.E. Lovell🇺🇸 · A.T. Mohan · P. Talou🇺🇸
May 8, 20202005.03198nucl-thJ.Phys.G32 citations

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Mohan, Arvind T.

Rapid Uncertainty Quantification on a Latent Field using Fisher Information

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

Quantifying Uncertainties on Fission Fragment Mass Yields With Mixture Density Networks