Validation and extrapolation of atomic mass with physics-informed fully connected neural network | Paper Citation Record

Observation a3b03b6c-63a1-4c42-a208-eb4377283fd8 · outbound

This paper cites Input and output features in Method I, II, and III.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Input and output features in Method I, II, and III

Reference 1

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Validation and extrapolation of atomic mass with physics-informed fully connected neural network Unresolved cited work

Reference 2

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This paper cites black box.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network black box

Reference 3

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Observation 516401a3-485b-4d06-83a3-3e1a535b3b67 · outbound

This paper cites Recent trends in the determination of nuclear masses,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Recent trends in the determination of nuclear masses,

Reference 4

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This paper cites Impact of nuclear mass uncertainties on the r-process,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Impact of nuclear mass uncertainties on the r-process,

Reference 5

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This paper cites Modern Theory of Nuclear Forces,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Modern Theory of Nuclear Forces,

Reference 6

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This paper cites The equation of state for nucleon matter and neutron star structure.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The equation of state for nucleon matter and neutron star structure

Reference 7

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This paper cites Equation of state of stellar nuclear matter and the effective nucleon mass,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Equation of state of stellar nuclear matter and the effective nucleon mass,

Reference 8

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Observation 3de327b8-2f8d-4e2c-91ba-68b85748296d · outbound

This paper cites Nuclear masses and deformations,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear masses and deformations,

Reference 9

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This paper cites Synthesis of the elements in stars,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Synthesis of the elements in stars,

Reference 10

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Observation 3b57d28a-5965-404b-ad81-8a7af40023c6 · outbound

This paper cites The impact of individual nuclear prop- erties on r-process nucleosynthesis,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The impact of individual nuclear prop- erties on r-process nucleosynthesis,

Reference 11

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This paper cites rp-process nucleosynthesis at extreme temperature and density conditions,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network rp-process nucleosynthesis at extreme temperature and density conditions,

Reference 12

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Observation 00f93616-b036-4a27-b084-2224c009de89 · outbound

This paper cites Location of the Neutron Dripline at Fluorine and Neon,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Location of the Neutron Dripline at Fluorine and Neon,

Reference 13

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This paper cites The limits of the nuclear landscape,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The limits of the nuclear landscape,

Reference 14

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Observation c8f4ef43-c7e9-4501-bae5-ae9b689617b3 · outbound

This paper cites The History of nuclidic masses and of their evaluation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The History of nuclidic masses and of their evaluation,

Reference 15

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Observation 17f15bf3-af72-44d5-accc-226028a0c35f · outbound

This paper cites The Ame 2003 atomic mass evaluation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The Ame 2003 atomic mass evaluation,

Reference 16

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Observation 1d673312-ba13-4865-a09f-0d98936695f4 · outbound

This paper cites The Ame2003 atomic mass evaluation (II). Tables, graphs and references,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The Ame2003 atomic mass evaluation (II). Tables, graphs and references,

Reference 17

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Observation f2d2709e-2e3b-44e2-b273-afd29a9d5541 · outbound

This paper cites The Ame2012 atomic mass evaluation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The Ame2012 atomic mass evaluation,

Reference 18

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Observation ea21941e-bf43-4944-9270-3b8455fbeb42 · outbound

This paper cites The Ame2012 atomic mass evaluation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The Ame2012 atomic mass evaluation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.916261Z

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Observation 46c8bbdb-05b6-462c-ba1d-1c09060d729a · outbound

This paper cites The AME2016 atomic mass evaluation (I). Evaluation of in- put data; and adjustment procedures,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The AME2016 atomic mass evaluation (I). Evaluation of in- put data; and adjustment procedures,

Reference 20

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Observation bb7a0b95-1bbb-443f-9613-0e8db92014b8 · outbound

This paper cites Nuclear Physics A. Sta- tionary States of Nuclei,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear Physics A. Sta- tionary States of Nuclei,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.887299Z

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Observation 8f2644d8-7155-4e06-a28a-4530f2fdca97 · outbound

This paper cites Zur Theorie der Kernmassen,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Zur Theorie der Kernmassen,

Reference 22

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Observation 0b5bc6aa-f068-4beb-b73c-1445c92394a1 · outbound

This paper cites Nuclear mass predictions with machine learning reaching the accuracy required by r-process studies,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass predictions with machine learning reaching the accuracy required by r-process studies,

Reference 23

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Observation 8dc65967-d4ff-4a3b-9f0b-c248a062b64d · outbound

This paper cites Nuclear ground-state masses and deformations: FRDM(2012),.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear ground-state masses and deformations: FRDM(2012),

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.842522Z

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Observation 9f7322ea-b5f6-4930-8c83-7088c59855a5 · outbound

This paper cites Nuclear mass formula via an approximation to the Hartree—Fock method,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass formula via an approximation to the Hartree—Fock method,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.828721Z

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Observation 6e3df810-6c06-48bf-a687-b451af2bb22a · outbound

This paper cites Further ex- plorations of Skyrme-Hartree-Fock-Bogoliubov mass for- mulas. 13. The 2012 atomic mass evaluation and the sym- 12 metry coefficient,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Further ex- plorations of Skyrme-Hartree-Fock-Bogoliubov mass for- mulas. 13. The 2012 atomic mass evaluation and the sym- 12 metry coefficient,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.814010Z

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Observation 6c67b6ac-ce52-45f6-9e77-179dc3c1435e · outbound

This paper cites Sur- face diffuseness correction in global mass formula,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Sur- face diffuseness correction in global mass formula,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.799204Z

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Observation 449f06cb-0f8a-4ee1-8f38-336d3c347a52 · outbound

This paper cites Relativistic mean field in finite nuclei,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Relativistic mean field in finite nuclei,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.783062Z

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Observation 4e2cdf75-1b67-41f5-8c6c-fbeea71e8721 · outbound

This paper cites Relativistic Hartree Bogoliubov theory: static and dynamic aspects of exotic nuclear structure,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Relativistic Hartree Bogoliubov theory: static and dynamic aspects of exotic nuclear structure,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.761849Z

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Observation 1a9f2e06-f87a-466e-aaac-27f172e1c223 · outbound

This paper cites Multidimensionally constrained covari- ant density functional theories—nuclear shapes and po- tential energy surfaces,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Multidimensionally constrained covari- ant density functional theories—nuclear shapes and po- tential energy surfaces,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.747076Z

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Observation 887786e1-9a1e-4477-bafa-c566e2239ab5 · outbound

This paper cites The limits of the nuclear landscape ex- plored by the relativistic continuum Hartree–Bogoliubov theory,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The limits of the nuclear landscape ex- plored by the relativistic continuum Hartree–Bogoliubov theory,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.729848Z

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Observation 8b6d20f8-d4e5-4dc3-a3ab-e173b199bd14 · outbound

This paper cites New parametrization for the nuclear covariant energy density functional with point-coupling interaction,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network New parametrization for the nuclear covariant energy density functional with point-coupling interaction,

Reference 32

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Observation 0cbf1976-e1aa-40b4-ad18-5fa76f0033f6 · outbound

This paper cites Nuclear mass table in deformed relativistic Hartree–Bogoliubov theory in continuum, I: Even–even nuclei,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass table in deformed relativistic Hartree–Bogoliubov theory in continuum, I: Even–even nuclei,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.701411Z

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Observation 1bc1572a-63f1-4642-be9f-422558242943 · outbound

This paper cites Nuclear mass table in deformed relativistic Hartree–Bogoliubov theory in continuum, II: Even-Z nuclei,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass table in deformed relativistic Hartree–Bogoliubov theory in continuum, II: Even-Z nuclei,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.687058Z

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Observation 70ff62d4-f1c9-4ca5-a665-e05f96d91288 · outbound

This paper cites Refining mass formulas for astrophysical applications: a Bayesian neu- ral network approach,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Refining mass formulas for astrophysical applications: a Bayesian neu- ral network approach,

Reference 35

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Observation 1407fa9b-80d3-4c9e-8607-e0da8303108c · outbound

This paper cites Global prediction of nuclear charge density dis- tributions using a deep neural network,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Global prediction of nuclear charge density dis- tributions using a deep neural network,

Reference 36

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Observation f0110427-c555-450f-b436-3255c88642fe · outbound

This paper cites Nuclear mass predictions based on convolutional neural network,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass predictions based on convolutional neural network,

Reference 37

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Observation 76869639-2b99-403c-a7b8-28168ea2d877 · outbound

This paper cites Validating neural- network refinements of nuclear mass models,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Validating neural- network refinements of nuclear mass models,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.642631Z

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Observation 079b2066-0460-47ac-b9c4-1fea5f8739c2 · outbound

This paper cites Deep learning approach to nuclear masses and α-decay half-lives,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Deep learning approach to nuclear masses and α-decay half-lives,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.629165Z

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Observation ea727031-3b19-4f71-9a9d-737fb5a6829c · outbound

This paper cites Nuclear binding energies in artificial neural networks,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear binding energies in artificial neural networks,

Reference 40

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Observation 27dda094-1340-4f46-a2b1-315fe470055f · outbound

This paper cites Predictions of nuclear charge radii and physical interpretations based on the naive Bayesian probability classifier,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Predictions of nuclear charge radii and physical interpretations based on the naive Bayesian probability classifier,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.599862Z

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Observation 78ecb35e-61fa-4ff6-8415-4575e80180e9 · outbound

This paper cites Novel Bayesian neural network based approach for nuclear charge radii,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Novel Bayesian neural network based approach for nuclear charge radii,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.582458Z

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Observation 2b052b29-adc1-463c-848a-103e8f3fbd03 · outbound

This paper cites Predictions of nuclearβ -decay half-lives with machine learning and their impact on r -process nucle- osynthesis,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Predictions of nuclearβ -decay half-lives with machine learning and their impact on r -process nucle- osynthesis,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.562718Z

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Observation b1d26608-7489-4515-a1fa-8adaf49f4b64 · outbound

This paper cites Bayesian optimization approach to model-based description of α decay,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Bayesian optimization approach to model-based description of α decay,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.545095Z

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Observation b4df252d-9671-49b9-a2bc-d4c42fc16320 · outbound

This paper cites Simple deep-learning approach for α-decay half-life studies,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Simple deep-learning approach for α-decay half-life studies,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.524506Z

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Observation b7fc624e-f63f-4375-bb1c-3ea675d0f025 · outbound

This paper cites Comprehensive estimation of nuclide production cross sections using a phenomenological approach,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Comprehensive estimation of nuclide production cross sections using a phenomenological approach,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.508722Z

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Observation b3d3d09a-bca1-4ef2-ac0c-23fc4ada17c9 · outbound

This paper cites Unmasking Cor- relations in Nuclear Cross Sections with Graph Neural Networks,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Unmasking Cor- relations in Nuclear Cross Sections with Graph Neural Networks,

Reference 47

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This paper cites Transfer learning and neural networks in predicting quadrupole deformation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Transfer learning and neural networks in predicting quadrupole deformation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.489345Z

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Observation a42d3a07-7344-4a91-910f-0f181b1dc91f · outbound

This paper cites Mapping low-lying states and B(E2;01+→21+) in even- even nuclei with machine learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Mapping low-lying states and B(E2;01+→21+) in even- even nuclei with machine learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.475421Z

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Observation d0c60bf0-8fdd-49a5-b283-64571c4cb3d1 · outbound

This paper cites A neural network approach for orienting heavy-ion collision events,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network A neural network approach for orienting heavy-ion collision events,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.461555Z

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Observation a9f1ee82-7c48-4076-9656-b300fd6b4389 · outbound

This paper cites Phase Transition Study Meets Machine Learn- ing,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Phase Transition Study Meets Machine Learn- ing,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.443825Z

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Observation 60a1db12-3abe-4857-a78a-91c9d1148c47 · outbound

This paper cites High-energy nuclear physics meets machine learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network High-energy nuclear physics meets machine learning,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.426371Z

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Observation 50ede56e-8979-4c81-a62c-852460e38a96 · outbound

This paper cites Exploring QCD matter in extreme conditions with Machine Learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Exploring QCD matter in extreme conditions with Machine Learning,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.407873Z

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Observation a3b442ce-a3d6-4c64-a83c-dee7700185c1 · outbound

This paper cites Machine learning study to identify collective flow in small and large colliding systems,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Machine learning study to identify collective flow in small and large colliding systems,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.392248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7ea7ac51-0ceb-4218-949e-418df7d1c5c6 · outbound

This paper cites Nuclear liquid-gas phase transition with machine learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear liquid-gas phase transition with machine learning,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.373322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 076dffb6-2b87-4fa8-b5a9-ac3f5ea0a17d · outbound

This paper cites Determining the temperature in heavy-ion collisions with multiplicity distribution.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Determining the temperature in heavy-ion collisions with multiplicity distribution

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:33:43.675185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 887a9740-c37d-4306-b0b9-faa06941c5d8 · outbound

This paper cites Properties of the QCD matter: re- view of selected results from the relativistic heavy ion collider beam energy scan (RHIC BES) program,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Properties of the QCD matter: re- view of selected results from the relativistic heavy ion collider beam energy scan (RHIC BES) program,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.356238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 34ca0607-5f28-40d2-b73d-5fe0cbf1d7c3 · outbound

This paper cites Properties of QCD matter: a review of selected results from ALICE experiment,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Properties of QCD matter: a review of selected results from ALICE experiment,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.339958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a8be32a7-f720-4c62-bdac-7037cb62ab82 · outbound

This paper cites Studies on several prob- lems in nuclear physics by using machine learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Studies on several prob- lems in nuclear physics by using machine learning,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.324924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0a5611a0-8fb4-4f6e-901e-d22174f5965b · outbound

This paper cites Machine learning in nuclear physics at low and intermediate energies,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Machine learning in nuclear physics at low and intermediate energies,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.308679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 389b9bcc-51fd-430e-a5d2-8688c7d1c885 · outbound

This paper cites Nuclear binding energy predictions using neural net- works: Application of the multilayer perceptron,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear binding energy predictions using neural net- works: Application of the multilayer perceptron,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.289379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ac2d253e-bed0-4741-a89b-6f43a4bc1b2d · outbound

This paper cites Correction to: Ma- chine learning the nuclear mass,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Correction to: Ma- chine learning the nuclear mass,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.268738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1d7c714d-d928-4cd8-af31-07ece9dbfc77 · outbound

This paper cites Nuclear mass predictions using machine learning mod- els,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear mass predictions using machine learning mod- els,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.249043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 92d72d9c-2f68-439b-9b4b-975a78cda8ba · outbound

This paper cites Bayesian approach to model-based ex- trapolation of nuclear observables,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Bayesian approach to model-based ex- trapolation of nuclear observables,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.230649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8705e48f-0474-4162-a62a-4194106dc419 · outbound

This paper cites On the rate of con- vergence of fully connected deep neural network regres- sion estimates,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network On the rate of con- vergence of fully connected deep neural network regres- sion estimates,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.214713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 67713bde-607f-4a3c-a995-c176c0d5be1e · outbound

This paper cites Multilayer feedforward networks are universal approxi- mators,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Multilayer feedforward networks are universal approxi- mators,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.197358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 54b71dca-db8d-4160-a8b8-d9862d031782 · outbound

This paper cites The AME 2020 atomic mass evaluation (II). Tables, graphs and references,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The AME 2020 atomic mass evaluation (II). Tables, graphs and references,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:43.335172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e470a97f-a083-45ba-8f46-58aad0facf0f · outbound

This paper cites The AME2016 atomic mass evaluation (II). Tables, graphs and references,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network The AME2016 atomic mass evaluation (II). Tables, graphs and references,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.166152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cf0b4f32-2df5-4385-9ae8-8375e42d1f7c · outbound

This paper cites Mirror nuclei constraint in mass formula,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Mirror nuclei constraint in mass formula,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.151083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 28b01ed0-0e4a-4a40-846b-a58c88f233ec · outbound

This paper cites Microscopic mass formulae.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Microscopic mass formulae

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:33:43.653133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9adc1679-b5e5-4261-aacf-e18d2303bb0a · outbound

This paper cites Nuclear magic numbers: new features far from stability.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Nuclear magic numbers: new features far from stability

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:43.351656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c851886-5fef-4c7b-9b6f-f565f54123b4 · outbound

This paper cites Self-consistent mean-field models for nuclear structure,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Self-consistent mean-field models for nuclear structure,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.136528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 58f28bf7-71cd-477d-9e48-f4e752316277 · outbound

This paper cites Relativistic Continuum Hartree Bogoli- ubov theory for ground state properties of exotic nuclei,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Relativistic Continuum Hartree Bogoli- ubov theory for ground state properties of exotic nuclei,

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:43.361514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65025790-5c6c-4e3a-bf8c-39f7883eab18 · outbound

This paper cites 261 (Springer, 1996).

Validation and extrapolation of atomic mass with physics-informed fully connected neural network 261 (Springer, 1996)

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.121504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d05d0fb2-7ce4-4cc9-bc3c-bf1697819277 · outbound

This paper cites Learning from noisy labels with deep neural networks: A survey,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Learning from noisy labels with deep neural networks: A survey,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.106775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc79791c-9b83-44be-a783-35b4416bacb8 · outbound

This paper cites Residual correla- tion in graph neural network regression,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Residual correla- tion in graph neural network regression,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.091931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72ea8255-b0b5-4707-b3d6-96887a816402 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Gaussian Error Linear Units (GELUs)

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:43.380801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4576a77f-76e4-433c-ad81-d5d2050e5de0 · outbound

This paper cites GELU Activation Function in Deep Learning: A Comprehensive Mathematical Analysis and Performance.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network GELU Activation Function in Deep Learning: A Comprehensive Mathematical Analysis and Performance

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:43.386209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80e841aa-eb2d-457c-b5ff-1fefc2214f01 · outbound

This paper cites Robust Estimation of a Location Pa- rameter,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Robust Estimation of a Location Pa- rameter,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.076492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e3d8ce1-579d-490c-b84a-487808c6145f · outbound

This paper cites Bayesian infer- ence of the crust-core transition density via the neutron- star radius and neutron-skin thickness data,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Bayesian infer- ence of the crust-core transition density via the neutron- star radius and neutron-skin thickness data,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.061559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 000af932-781b-4e96-95dc-5dbd99564175 · outbound

This paper cites Bayesian inference of neutron- skin thickness and neutron-star observables based on ef- fective nuclear interactions,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Bayesian inference of neutron- skin thickness and neutron-star observables based on ef- fective nuclear interactions,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.048049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f248ed7f-c692-4ef9-9e39-f5141737eeb8 · outbound

This paper cites Bayesian model averaging (BMA) for nuclear data evaluation,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Bayesian model averaging (BMA) for nuclear data evaluation,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.034388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ad31a104-9618-4abb-b0c8-dc241a9f24f9 · outbound

This paper cites Impact parameter dependence of anisotropic flow: Bayesian reconstruction in ultracentral nucleus-nucleus collisions,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Impact parameter dependence of anisotropic flow: Bayesian reconstruction in ultracentral nucleus-nucleus collisions,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.020278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d1296886-9df3-4d86-9aeb-614193ccd043 · outbound

This paper cites Measurement of the mass dif- ference and the binding energy of the hypertriton and antihypertriton,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Measurement of the mass dif- ference and the binding energy of the hypertriton and antihypertriton,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:44.005537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6a4f5a67-7bf0-40d3-a899-a3b58184d958 · outbound

This paper cites Imaging shapes of atomic nuclei in high-energy nuclear collisions,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Imaging shapes of atomic nuclei in high-energy nuclear collisions,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.989694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 261af23d-b1b7-44a1-8083-271b116fc0fc · outbound

This paper cites Imaging the initial condition of heavy-ion collisions and nuclear structure across the nu- clide chart,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Imaging the initial condition of heavy-ion collisions and nuclear structure across the nu- clide chart,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.974660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 26048853-f544-463f-8b45-bd0c51264999 · outbound

This paper cites Evidence of Quadrupole and Octupole Deformations in Zr 96+Zr96 and Ru96+Ru96 Collisions at Ultrarelativistic Energies,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Evidence of Quadrupole and Octupole Deformations in Zr 96+Zr96 and Ru96+Ru96 Collisions at Ultrarelativistic Energies,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.959455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 41a5777b-c594-4df2-b2ff-0994c82f5edb · outbound

This paper cites Impact of Nuclear Deformation on Relativistic Heavy- Ion Collisions: Assessing Consistency in Nuclear Physics across Energy Scales,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Impact of Nuclear Deformation on Relativistic Heavy- Ion Collisions: Assessing Consistency in Nuclear Physics across Energy Scales,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.944310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b52d98bf-b8f7-476a-9ce4-f23f01712a78 · outbound

This paper cites Interpretable deep learning for nuclear deformation in heavy ion collisions.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Interpretable deep learning for nuclear deformation in heavy ion collisions

Reference 89

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:33:43.505787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 53474a83-362f-46d3-afb9-215701736a98 · outbound

This paper cites Deep-neural-network approach to solving the ab initio nuclear structure prob- lem,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Deep-neural-network approach to solving the ab initio nuclear structure prob- lem,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.928377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6751547e-6124-4649-b926-fb3cf0e4f71b · outbound

This paper cites Beyond axial symmetry: high- energy collisions unveil the ground-state shape of 238U,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Beyond axial symmetry: high- energy collisions unveil the ground-state shape of 238U,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.912791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7921aaf2-27d6-4ef3-92f6-d59d82dcd27f · outbound

This paper cites Applications of deep learning to relativistic hydrodynamics,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Applications of deep learning to relativistic hydrodynamics,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.897218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 70f1937b-62f4-489f-970a-34928b40ea6f · outbound

This paper cites An equation-of- state-meter of quantum chromodynamics transition from deep learning,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network An equation-of- state-meter of quantum chromodynamics transition from deep learning,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.881166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 48191bab-d6f7-4dbf-8ff4-f4b3c4ea6a6b · outbound

This paper cites Deep-learning quasi-particle masses from QCD equation of state,.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Deep-learning quasi-particle masses from QCD equation of state,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:33:43.864786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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