Paper Citation Record · LEDGER

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks

As of 23 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 3 inbound Pith citation observations for arXiv:2505.12557.

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

pith.paper-citation-record.v1
2505.12557 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:37:54.738699Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:37:54.604398Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:41:27.436573Z

Reference resolution

28 of 28 outbound references displayed

verified exact0
verified fuzzy23
unresolved5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c50457fc-f280-466f-b9d2-ef77fb355608 · outbound

This paper cites Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:37:54.604398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation effe8404-b2e6-4c9f-8bf6-44c54f187393 · outbound

This paper cites K is the bulk modulus, and ρ is the air density.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks K is the bulk modulus, and ρ is the air density

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.239755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d3793380-b0ef-4f45-ac05-2de638d9ab27 · outbound

This paper cites The neural network architecture is similar to that in [6], as shown in Fig.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks The neural network architecture is similar to that in [6], as shown in Fig

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.222203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 400b601f-b8ab-4e5a-a725-4832d4bdfb73 · outbound

This paper cites The numbers of collection points areNPDE = 5000 andNBC =NPC = NO = 1000.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks The numbers of collection points areNPDE = 5000 andNBC =NPC = NO = 1000

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.203662Z

Source-reported events for the cited work

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Observation cc64ea8b-5e1a-4a9d-9e87-af8ca8cfef50 · outbound

This paper cites an unresolved cited work.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:37:55.185101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 077d7052-3364-47d1-a530-783fefdac2f3 · outbound

This paper cites Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse prob- lems involving nonlinear partial differential equa- tions,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse prob- lems involving nonlinear partial differential equa- tions,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.167852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c6146268-b01e-4be9-ab14-e391b92a3ede · outbound

This paper cites A physics-informed neural network approach for nearfield acoustic holography,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks A physics-informed neural network approach for nearfield acoustic holography,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:37:54.634739Z

Source-reported events for the cited work

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Observation aa8ea989-05b5-4485-b28b-39d9a9af9ebb · outbound

This paper cites Complex-valued physics-informed neural network for near-field acoustic holography,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Complex-valued physics-informed neural network for near-field acoustic holography,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.138319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 206d5eba-7afa-408d-80da-298a7b12bb65 · outbound

This paper cites Physics-informed neural networks for acoustic boundary admittance estimation,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Physics-informed neural networks for acoustic boundary admittance estimation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.123136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a7b758a-b5c8-495d-b410-974838c0b38c · outbound

This paper cites Room impulse response reconstruction with physics-informed deep learning,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Room impulse response reconstruction with physics-informed deep learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.107733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9680e2f6-d255-4d86-8563-a3400fe63d75 · outbound

This paper cites Physics- informed neural network for acoustic resonance anal- ysis in a one-dimensional acoustic tube,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Physics- informed neural network for acoustic resonance anal- ysis in a one-dimensional acoustic tube,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.092131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 834d0ae8-0f2b-4a37-8650-8495da391174 · outbound

This paper cites Synthesis of voiced sounds using physics-informed neural net- works,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Synthesis of voiced sounds using physics-informed neural net- works,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.075865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6ed51e6e-2bcc-4a81-8de4-e4f60778cc2d · outbound

This paper cites Physics-informed cnn for the design of acoustic equipment,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Physics-informed cnn for the design of acoustic equipment,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.059724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 971891f1-a4f2-489e-a15c-d122cbcbeeec · outbound

This paper cites Identification of physical properties in acoustic tubes using physics- informed neural networks,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Identification of physical properties in acoustic tubes using physics- informed neural networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.042594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 781ef0cf-eb74-476d-9eb1-0e7617c20e9e · outbound

This paper cites Approximation formulae for the acoustic radiation impedance of a cylindrical pipe,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Approximation formulae for the acoustic radiation impedance of a cylindrical pipe,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.026312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 66ff6854-f33a-435d-b9b8-2ce181712a86 · outbound

This paper cites Acoustical analysis of the chinese transverse flute (dizi) using the transfer matrix method,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Acoustical analysis of the chinese transverse flute (dizi) using the transfer matrix method,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:55.009890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 84d4a419-e38c-46af-8fd5-268952d74337 · outbound

This paper cites Dissipative time- domain one-dimensional model for viscothermal acoustic propagation in wind instruments,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Dissipative time- domain one-dimensional model for viscothermal acoustic propagation in wind instruments,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.992153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 868f1471-620b-40e7-85e9-215b5c98bbff · outbound

This paper cites Time-domain simu- lation of a dissipative reed instrument,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Time-domain simu- lation of a dissipative reed instrument,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.973524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5a2cc59-7122-4507-8b26-62e94af71fc1 · outbound

This paper cites Elementary sources and multipoles,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Elementary sources and multipoles,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.956625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4fafba30-b07a-4149-980e-98d295c8e784 · outbound

This paper cites an unresolved cited work.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:37:54.940743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5d93801a-665a-4d46-a666-08c677c1a79f · outbound

This paper cites Neural networks fail to learn periodic functions and how to fix it,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Neural networks fail to learn periodic functions and how to fix it,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.925841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b64a5371-57b4-4936-a693-ab626f5bc8af · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional do- mains,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Fourier features let networks learn high frequency functions in low dimensional do- mains,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.908908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a0196cfa-a508-4c4a-991f-ac8b20054842 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Adam: A Method for Stochastic Optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T20:37:54.714216Z

Source-reported events for the cited work

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Observation da842129-ea6a-41ad-8120-c8066e3e968a · outbound

This paper cites On the limited memory bfgs method for large scale optimization,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks On the limited memory bfgs method for large scale optimization,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.888976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 62d24c83-d114-4527-bade-97761d2608b6 · outbound

This paper cites Random fourier features pytorch,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Random fourier features pytorch,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.872318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8a4a4f2f-b406-48e4-a4bb-8298831e7cb7 · outbound

This paper cites Characterizing possible fail- ure modes in physics-informed neural networks,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Characterizing possible fail- ure modes in physics-informed neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.854081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e3ce6208-c97a-460c-bcfd-ed44f5a68a7e · outbound

This paper cites Reconstruction of an acoustic pressure field in a resonance tube by parti- cle image velocimetry,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Reconstruction of an acoustic pressure field in a resonance tube by parti- cle image velocimetry,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.836865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 46b0d7cc-e156-47e4-901e-eb29c35d5d8e · outbound

This paper cites Estimates on the general- ization error of physics-informed neural networks for approximating a class of inverse problems for pdes,.

Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks Estimates on the general- ization error of physics-informed neural networks for approximating a class of inverse problems for pdes,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:37:54.817870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation c50457fc-f280-466f-b9d2-ef77fb355608 · inbound