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Paper Citation Record · LEDGER

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.15363.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.15363 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:24:25.753331Z

measured 34 of 34 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 61eeddbf-109e-490d-b2ac-29856afea946 · outbound

This paper cites Lunney, J.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Lunney, J

Reference 1

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Observation 3bc3278f-9ffe-437e-ad3b-3508f9ba0bfe · outbound

This paper cites Myers, W.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Myers, W

Reference 2

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Observation 68e62402-59cd-4fe6-a5d8-fc4ec7eada8a · outbound

This paper cites an unresolved cited work.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 3

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Observation 761c0d02-8bb5-4c69-ae21-03e53246c375 · outbound

This paper cites Koura, T.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Koura, T

Reference 4

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Observation 12e76030-07c1-4c0e-807b-9dc79d04f4f8 · outbound

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 5

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Observation e150386b-ccbb-4f55-9c5d-71d72e07b4bd · outbound

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

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Nuclear ground-state masses and deformations: FRDM(2012)

Reference 6

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Observation e7b1addd-0d45-4f3c-bef7-55158350a7c7 · outbound

This paper cites Utama, J.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Utama, J

Reference 7

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 8

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Observation 11dec650-cde8-46fc-88d2-f131b23aa498 · outbound

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 9

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 10

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Observation 73a26d4c-44f8-4c53-8579-559ee2c8514d · outbound

This paper cites Boehnlein, M.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Boehnlein, M

Reference 11

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Observation cc1d9b9b-7270-41c6-adef-2f913e4c1692 · outbound

This paper cites Barnard, L.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Barnard, L

Reference 12

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Observation e355cad7-4165-495f-933e-698ec1c32f63 · outbound

This paper cites Haley, D.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Haley, D

Reference 13

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Observation 6511909a-35d2-4f6b-b4c3-faaa5a101279 · outbound

This paper cites Extrapolation and learning equations.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Extrapolation and learning equations

Reference 14

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This paper cites Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks

Reference 15

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 16

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Observation f3e27f73-aac5-456b-875b-623a9b015609 · outbound

This paper cites Learning Sparse Neural Networks through $L_0$ Regularization.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Learning Sparse Neural Networks through $L_0$ Regularization

Reference 17

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 18

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Observation 0e418936-bcf2-466d-b1dc-ae56653757fb · outbound

This paper cites Buhrmester, D.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Buhrmester, D

Reference 19

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Observation 14ec0c4d-8664-41e1-970c-77027d7ee347 · outbound

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 20

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Observation 1606e72e-c5e3-47bc-a23d-635ce361337d · outbound

This paper cites Schmidt, H.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Schmidt, H

Reference 21

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This paper cites Specifically, the bound range of mass excesses was set to [−0.1, 2] u (atomic mass unit) by defining B1, B2=0.95, 1.05 u.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Specifically, the bound range of mass excesses was set to [−0.1, 2] u (atomic mass unit) by defining B1, B2=0.95, 1.05 u

Reference 22

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This paper cites Udrescu, M.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Udrescu, M

Reference 23

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This paper cites Sahoo, C.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Sahoo, C

Reference 24

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 25

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Informed Equation Learning

Reference 26

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 27

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 28

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 29

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 30

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Lakshminarayanan, A

Reference 31

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 32

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Observation 1fa14915-1b43-434b-9f9f-df55b1c3526e · outbound

This paper cites Vaswani, N.

Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Vaswani, N

Reference 34

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Robust extrapolation using physics-related activation functions in neural networks for nuclear masses Unresolved cited work

Reference 210

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