Paper Citation Record · LEDGER

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions

As of 22 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2412.20192.

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

pith.paper-citation-record.v1
2412.20192 v2

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measured 74 of 74 reference resolution

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One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:34:41.548794Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

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Reference resolution

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External citation measurements

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Outbound references

Observation d03dcec4-634c-42a3-a6a7-f1a1af64b154 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 2

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Observation 3d557811-d05b-4a82-b3da-705cd80757fd · outbound

This paper cites & Zimmerman, G.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Zimmerman, G

Reference 3

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Observation 4fab6be9-9f2e-4650-82fa-671f7b5c6d08 · outbound

This paper cites & Harte, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Harte, J

Reference 4

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Source-reported events for the cited work

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Observation 305c158e-ffa5-4a4b-90cd-75ae621a87b4 · outbound

This paper cites InAPS Division of Plasma Physics Meeting Abstracts, vol.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions InAPS Division of Plasma Physics Meeting Abstracts, vol

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:38.002770Z

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Observation 627c088c-6a51-4de6-a51b-ba7c5c1ca64c · outbound

This paper cites M.et al.The development of a high-resolution eulerian radiation-hydrodynamics simulation capability for laser-driven hohlraums.Phys.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions M.et al.The development of a high-resolution eulerian radiation-hydrodynamics simulation capability for laser-driven hohlraums.Phys

Reference 6

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Source-reported events for the cited work

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Observation a1c5d857-aece-4766-ac10-19edd8d882c5 · outbound

This paper cites M., Thompson, S.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions M., Thompson, S

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.983851Z

Source-reported events for the cited work

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Observation 838ac3a7-f125-499c-af4a-e8fe7252c80f · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 8

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Observation 991765cc-e6b5-42d3-bd0e-d66644d5c9ff · outbound

This paper cites & Weatherby, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Weatherby, J

Reference 9

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Observation 5b5df56c-0551-4cc6-82b9-cadf1b20ceb5 · outbound

This paper cites review letters129, 075001 (2022).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions review letters129, 075001 (2022)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.951292Z

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Observation 954b882c-de81-4d51-80a6-a0c4d3b4886b · outbound

This paper cites 13.Lindl, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions 13.Lindl, J

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.941625Z

Source-reported events for the cited work

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Observation 2fe1f9a3-81e6-46bf-8961-ec3c05fdc7c8 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 16

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Observation 37787fd5-1445-4f29-a7b9-b1eb9e59b6db · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 17

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Observation 7e80f28a-e946-4950-a6f5-c66d7cdefad2 · outbound

This paper cites & Hollenbach, R.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Hollenbach, R

Reference 18

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Observation fbe7aa17-ab2a-44cc-bc81-d353622f9023 · outbound

This paper cites M.et al.Overview of the line-imaging visar diagnostic at the national ignition facility (nif).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions M.et al.Overview of the line-imaging visar diagnostic at the national ignition facility (nif)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.904028Z

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Observation c7f6be16-3f19-4205-8deb-9955aa87a650 · outbound

This paper cites scientific instruments75, 4916–4929 (2004).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions scientific instruments75, 4916–4929 (2004)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.894460Z

Source-reported events for the cited work

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Observation e8d4ece8-8e36-4be7-b468-2bd257904dba · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.884410Z

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Observation f1841be1-9ba6-422e-9eae-9af3653d00b3 · outbound

This paper cites J., Gust, W.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions J., Gust, W

Reference 22

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Observation e065b815-5578-4677-adef-f2e69ecd312d · outbound

This paper cites & Lipkin, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Lipkin, J

Reference 23

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Source-reported events for the cited work

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Observation 73740a82-3e0a-4c74-8655-a7b63fe855ec · outbound

This paper cites & Asay, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Asay, J

Reference 24

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Observation 1da41160-74c9-4d93-96ce-2f2d9eb4186a · outbound

This paper cites & Ding, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Ding, J

Reference 25

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Observation 226ee3d7-69e0-48fb-919c-45df5aea1001 · outbound

This paper cites F., Blewett, P.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions F., Blewett, P

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.837601Z

Source-reported events for the cited work

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Observation fd1a0452-46d2-4fab-8f23-2c54dd24e36f · outbound

This paper cites & Weber, S.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Weber, S

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.827202Z

Source-reported events for the cited work

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Observation e88cad16-b368-45e4-8ef8-02bfa046c4ed · outbound

This paper cites R., Cela, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions R., Cela, J

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.816503Z

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Observation 676147d3-d3cd-4197-80f1-217765893892 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 31

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Observation c7e38d55-e80f-45fd-b06d-53092f269608 · outbound

This paper cites review letters107, 264502 (2011).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions review letters107, 264502 (2011)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.791768Z

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Observation b8ce5f0c-e58f-43a1-93aa-bf444caa486b · outbound

This paper cites Fluid Mech.703, 60–84 (2012).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Fluid Mech.703, 60–84 (2012)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.781888Z

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Observation a53744e0-cfba-4fba-b05e-b725c70c6e8d · outbound

This paper cites L., Lombardini, M., Pullin, D.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions L., Lombardini, M., Pullin, D

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.771764Z

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Observation 8035df78-bb63-4ef6-8549-53103b9a7947 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.762874Z

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Observation b136f459-19e5-4762-b0bb-4901c805d970 · outbound

This paper cites B.et al.Using richtmyer–meshkov instabilities to estimate metal strength at very high rates.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions B.et al.Using richtmyer–meshkov instabilities to estimate metal strength at very high rates

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.754120Z

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Observation 9b42ce02-2a56-41c8-9dcb-a036c23d38d4 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.744264Z

Source-reported events for the cited work

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Observation e150b803-a3ed-4123-af04-43767180f49b · outbound

This paper cites Plasmas27(2020).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Plasmas27(2020)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.734979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 11d60744-d287-4223-b15d-ffccafa3c2c3 · outbound

This paper cites Experimental study of the initial conditions of the rayleigh-taylor instability at the ablation front in inertial confinement fusion.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Experimental study of the initial conditions of the rayleigh-taylor instability at the ablation front in inertial confinement fusion

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.725288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f3c54dd7-bb2a-4ac4-9963-e701b106150c · outbound

This paper cites Plasmas26 (2019).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Plasmas26 (2019)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.715832Z

Source-reported events for the cited work

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Observation 0dd4f9a7-a5cc-45cf-8bb4-01a3b9df9ad2 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.705902Z

Source-reported events for the cited work

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Observation cd22c227-a98a-4906-8095-7c2b11a19474 · outbound

This paper cites & Tommasini, R.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Tommasini, R

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.696345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c55e07ef-dc14-4d68-97a8-bd532437e9ce · outbound

This paper cites review letters74, 3608 (1995).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions review letters74, 3608 (1995)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.686811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 09eba4a9-7dd6-43b0-98ee-9526f0ca72e2 · outbound

This paper cites A., Klasky, M.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions A., Klasky, M

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T23:33:36.944549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bfbeb4c-815b-4467-8058-a77b18929d07 · outbound

This paper cites & Luo, X.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Luo, X

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.677804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9b2ef7ed-bc0c-4994-893d-217cf4033b67 · outbound

This paper cites A.et al.Studying the richtmyer–meshkov instability in convergent geometry under high energy density conditions using the decel platform.Phys.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions A.et al.Studying the richtmyer–meshkov instability in convergent geometry under high energy density conditions using the decel platform.Phys

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.668530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cdb1dd57-9177-4d0b-b581-1f42f5995f78 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.658892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c6f9d6b5-c756-4312-8ef4-040803d743b6 · outbound

This paper cites & Luo, X.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Luo, X

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.648504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aee739fd-fe0a-42f0-bb6e-9aaf35e274cc · outbound

This paper cites Shock-interface interaction: current research on the Richtmyer-Meshkov problem.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Shock-interface interaction: current research on the Richtmyer-Meshkov problem

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.639395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e0eeeebb-822d-4589-b10a-b35b61aacfa9 · outbound

This paper cites D: Nonlinear Phenom.423, 132838 (2021).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions D: Nonlinear Phenom.423, 132838 (2021)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.630085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 01e378e3-62f4-4c34-ae3b-238dbfc537dc · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.620553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aac2d8fa-8bea-4e5c-82c0-d00c20cd221d · outbound

This paper cites L.et al.Richtmyer–Meshkov instability growth: experiment, simulation and theory.J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions L.et al.Richtmyer–Meshkov instability growth: experiment, simulation and theory.J

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.610639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 917cc2f3-e674-4d1a-983e-30a08cbc3c32 · outbound

This paper cites Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.600127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de423b0a-bc71-40f8-9ad6-1a5f85062d86 · outbound

This paper cites & Graham, M.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Graham, M

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.588449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 47e84acc-0709-4742-94ff-fc26ac103916 · outbound

This paper cites Express30, 14432–14452 (2022).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Express30, 14432–14452 (2022)

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.579179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c467407-1964-466e-b12a-00302df658ce · outbound

This paper cites D., Kolev, T.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions D., Kolev, T

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.569932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16c6da1b-3022-45bc-8530-a09b3a99cc6c · outbound

This paper cites A., Klasky, M., Burby, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions A., Klasky, M., Burby, J

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.560740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b61ff8ff-c3fb-4ccf-a67a-dfc4b10c377f · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.551263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fefba4e1-b9f9-43bc-bcb7-0eb7a647c0ea · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.540989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 006adfd5-3e8f-49d8-befb-34e26328d7ac · outbound

This paper cites & Liu, M.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Liu, M

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.531500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 736873c9-9e9c-4417-85d3-302316cd3792 · outbound

This paper cites T., Ghattas, O., Heinkenschloss, M.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions T., Ghattas, O., Heinkenschloss, M

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.521317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8658a4be-24ba-4374-8290-ddc5481321c9 · outbound

This paper cites K., Southworth, B.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions K., Southworth, B

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.510787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07cef435-2c5c-4fec-aa18-caa2407dadba · outbound

This paper cites & Karniadakis, G.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Karniadakis, G

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.501005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6d834030-3a3a-4813-9462-b2f89bd749dc · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.491355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9c4da2d0-e738-4757-85b5-642ee0316208 · outbound

This paper cites A.et al.Data-driven prediction of scaling and ignition of inertial confinement fusion experiments.Phys.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions A.et al.Data-driven prediction of scaling and ignition of inertial confinement fusion experiments.Phys

Reference 71

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.150907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c1113153-65a1-4917-bb65-b0a481fa449d · outbound

This paper cites & Libby, S.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Libby, S

Reference 72

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.140375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ce5281e2-c204-4d65-8726-d758c98de8ce · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T23:33:37.015618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 575f32e7-c53f-403f-aa8f-c7eeeeff7064 · outbound

This paper cites & Peterson, J.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Peterson, J

Reference 74

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.130124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 148e8999-9a21-4fb3-8368-b7214f5385ca · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 75

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.119334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e27dcf67-7400-4aae-bcc8-1b12b146edb0 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 76

Resolution: verified exact; raw_fallback, observed 2026-08-10T23:33:37.324096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 40ae36d8-0a22-4085-9fe2-2a5db5ea3d2e · outbound

This paper cites C.et al.Experimental study of energy transfer in double shell implosions.Phys.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions C.et al.Experimental study of energy transfer in double shell implosions.Phys

Reference 77

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.109071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c0ae8e80-2692-43bf-ae37-86717f909946 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.480711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a68684b-ee5c-4d42-84fc-c894e9247658 · outbound

This paper cites Ultramicroscopy157, 35–47, DOI: https://doi.org/10.1016/j.ultramic.2015.05.002 (2015).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Ultramicroscopy157, 35–47, DOI: https://doi.org/10.1016/j.ultramic.2015.05.002 (2015)

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-10T23:33:37.036343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d7236c8-2d7c-4f70-8e0d-d28cf59859a8 · outbound

This paper cites & Santana-Cedrés, D.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions & Santana-Cedrés, D

Reference 80

Resolution: verified exact; doi, observed 2026-08-10T23:33:37.092584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d2c744b-3c53-404b-aded-3c5eee66cf58 · outbound

This paper cites an unresolved cited work.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:33:37.469863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 578555f9-d2ef-42d2-a1d1-243e734a089d · outbound

This paper cites The sesame database.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions The sesame database

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.458687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 23638540-4027-4234-84d8-be373d028e02 · outbound

This paper cites In2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 16272–16282, DOI: 10.1109/CVPR52688.2022.01581 (2022).

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions In2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 16272–16282, DOI: 10.1109/CVPR52688.2022.01581 (2022)

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-10T23:33:37.050192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 307ecc99-08b4-49ed-96de-0d3ea51cd054 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-10T23:33:37.053699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7752ea30-4a4f-4d66-a113-a2dffdeb7c81 · outbound

This paper cites P., Marins, M.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions P., Marins, M

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.448077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d971a42-7013-4936-8eee-c4727e7471a6 · outbound

This paper cites P., Mohamed, S., Jimenez Rezende, D.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions P., Mohamed, S., Jimenez Rezende, D

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.437763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 203fde07-0e3d-4aec-8a17-b7dd82a8008d · outbound

This paper cites In Guyon, I.et al.(eds.)Advances in Neural Information Processing Systems, vol.

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions In Guyon, I.et al.(eds.)Advances in Neural Information Processing Systems, vol

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:33:37.427087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation dfdbdaa2-1ebc-4acb-b78f-7a7be41714f9 · inbound

Learning robust parameter inference and density reconstruction in flyer plate impact experiments cites this paper.

Learning robust parameter inference and density reconstruction in flyer plate impact experiments Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:34:45.094383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.