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Paper Citation Record · LEDGER

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network

As of 15 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2502.00897.

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

pith.paper-citation-record.v1
2502.00897 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:22:20.602446Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:04.178190Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:09:04.922990Z

Reference resolution

36 of 36 outbound references displayed

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  • verified fuzzy22
  • unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f6bd364-cbbc-4103-af7e-b8c922e0d8a3 · outbound

This paper cites Seismic modeling.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Seismic modeling

Reference 1

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no resolver link, observed 2026-08-09T17:22:20.493046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.493046Z digest=sha256:3468655ec1a8561672f65b5595b145daf8e2a509e65484bcf28c954aec0e309c

Observation 4403b8ae-03e6-4225-989f-da29e958da9c · outbound

This paper cites Full seismic waveform modelling and inversion.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Full seismic waveform modelling and inversion

Reference 2

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no resolver link, observed 2026-08-09T17:22:20.497082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.497082Z digest=sha256:924a8538bdeb28ff9263641d0571163be8b0cb480e724513d0489e5456fd3259

Observation 52a88a22-4702-47d1-a3bd-a7bb06869f54 · outbound

This paper cites Accuracy of finite-difference and finite-element modeling of the scalar and elastic wave equations.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Accuracy of finite-difference and finite-element modeling of the scalar and elastic wave equations

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.500547Z digest=sha256:447d3705f5e2702c6bb4af3cf908a17fb3327b4b526b23ee254c61b0cfe3e1cd

Observation b14896f2-1112-4e36-9ad7-67c20256bf9d · outbound

This paper cites Seismic waveform inversion in the frequency domain, part 1: Theory and verification in a physical scale model.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Seismic waveform inversion in the frequency domain, part 1: Theory and verification in a physical scale model

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.905573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.504148Z digest=sha256:5ba09009d090d2d7e9207408c1e6e9285dc23cf0479eb554a19b5ba64ecf05cd

Observation 63f4844a-db02-4bae-b0b3-4b240846ac28 · outbound

This paper cites Seismic waveform inversion in the frequency domain, part 2: Fault delineation in sediments using crosshole data.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Seismic waveform inversion in the frequency domain, part 2: Fault delineation in sediments using crosshole data

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.507881Z digest=sha256:4960507ed92cc3bba213e72bae8eef4ae6367921ae2ed2cef1d9fff4ada66a6b

Observation 07255a39-56a8-4378-bc2a-e357849d0db9 · outbound

This paper cites Frequency-domain elastic wave modeling by finite differences: A tool for crosshole seismic imaging.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Frequency-domain elastic wave modeling by finite differences: A tool for crosshole seismic imaging

Reference 6

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.511411Z digest=sha256:f4b23f31d27bab96b8c3e5d307b8c8b43c187673f637712a99bb692da8424b5c

Observation 8cef25aa-56c5-46f8-a048-2fb1999230c1 · outbound

This paper cites 3d finite-difference frequency-domain modeling of visco-acoustic wave propagation using a massively parallel direct solver: A feasibility study.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network 3d finite-difference frequency-domain modeling of visco-acoustic wave propagation using a massively parallel direct solver: A feasibility study

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.515076Z digest=sha256:73f6640439759bb887fd1445d3933e95deaec636bef12e947a2c6a0fa88c2ad9

Observation edd7157f-1896-43c9-bd36-948a9749419e · outbound

This paper cites A new iterative solver for the time-harmonic wave equation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network A new iterative solver for the time-harmonic wave equation

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.518522Z digest=sha256:d3a0392326c3467cbc69645feac73e2da85d1e816738e925599e99d0a76a7c2f

Observation 8273ba11-8546-44cd-acea-11ecc6909aa7 · outbound

This paper cites Three-dimensional frequency-domain full-waveform inversion with an iterative solver.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Three-dimensional frequency-domain full-waveform inversion with an iterative solver

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.521870Z digest=sha256:20278a75186cb79548a848cb7e30a4f36218a3e2002e87b3887012d4a4f59c8a

Observation 95b7d55f-15bf-42cb-b62b-908a158ad4be · outbound

This paper cites 3d finite-difference modeling of elastic wave propagation in the laplace-fourier domain.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network 3d finite-difference modeling of elastic wave propagation in the laplace-fourier domain

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.525085Z digest=sha256:1c74ccea7eb06537c9b1d7a223a303c0083405dc848f9689b8dbd30201978f23

Observation 3877b938-b860-44d5-acad-fcaabba231be · outbound

This paper cites An efficient helmholtz solver for acoustic transversely isotropic media.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network An efficient helmholtz solver for acoustic transversely isotropic media

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.528484Z digest=sha256:6472a56c10cba45601c867b6dcf680c0dee4a16cdd1b2a32cccd81966e597df9

Observation c09986ef-5dbd-4b4e-a178-7cf890a4c824 · outbound

This paper cites An optimal nearly analytic discrete method for 2d acoustic and elastic wave equations.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network An optimal nearly analytic discrete method for 2d acoustic and elastic wave equations

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.531887Z digest=sha256:2cf7abc56144320dbe538caa697e0f9135a737252be7d19d140dc2f040f3ee8a

Observation e2c50b71-129c-4781-9f02-328adedd8229 · outbound

This paper cites A finite-difference iterative solver of the helmholtz equation for frequency-domain seismic wave modeling and full-waveform inversion.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network A finite-difference iterative solver of the helmholtz equation for frequency-domain seismic wave modeling and full-waveform inversion

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.535283Z digest=sha256:4e677d273328606176ffcee9476d9104a5aa3b6227247424a00293304ea8ba3e

Observation 6a87ed3b-42dc-4f1e-8bc0-832c00e8fb46 · outbound

This paper cites Accelerating the shifted laplace preconditioner for the helmholtz equation by multilevel deflation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Accelerating the shifted laplace preconditioner for the helmholtz equation by multilevel deflation

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.810082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.538452Z digest=sha256:da862c567692966fee7b71516b4d8cdd086ca807f0d22b0640518b48b831c241

Observation cc551f6d-975e-4fb5-94b4-d27cb5a0a863 · outbound

This paper cites An iterative solver for the 3d helmholtz equation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network An iterative solver for the 3d helmholtz equation

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.800276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.541694Z digest=sha256:95ed33cae80154af96229fed94855f8bf7685d22ba2159fb27feaab878093937

Observation 6c89cbac-bcb5-4951-8f9b-60a8255a0ebc · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 16

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no resolver link, observed 2026-08-09T17:22:20.544756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.544756Z digest=sha256:992ada43ee1e243d932d4a1465417e2ab6d774eae4f2dd4b108f37b85b29dbc5

Observation e77976ab-4706-4318-a8d0-0d726bf3c745 · outbound

This paper cites Physics-informed neural networks (pinns) for wave propagation and full waveform inversions.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Physics-informed neural networks (pinns) for wave propagation and full waveform inversions

Reference 17

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no resolver link, observed 2026-08-09T17:22:20.547880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.547880Z digest=sha256:e129ede071c010d7af78424afde6f6a6ee425b17ed61daf74ca37f5bfd0d770a

Observation c32e33f5-8201-44f7-ac13-c334c598a970 · outbound

This paper cites Kronecker neural networks overcome spectral bias for pinn-based wavefield computation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Kronecker neural networks overcome spectral bias for pinn-based wavefield computation

Reference 18

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.550862Z digest=sha256:c353ea01faf2c7038c2f5fbd5aaa5f2bf232b096523eb61138794dee3a00cad5

Observation 5f500048-48c5-4539-8e50-292f77d08756 · outbound

This paper cites Multi-frequency wavefield modeling of acoustic vti wave equation using physics informed neural networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Multi-frequency wavefield modeling of acoustic vti wave equation using physics informed neural networks

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.554076Z digest=sha256:83dab754aa7eee6638d670aeb91749f407b138756bb4cf39865c6bce75d81e87

Observation bc4c1cc9-d26a-4e05-8270-8c511acac4ce · outbound

This paper cites Review of physics-informed machine-learning inversion of geophysical data.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Review of physics-informed machine-learning inversion of geophysical data

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.557222Z digest=sha256:068b7eed9b6a32eb8f53bebdf0e467bc077789bfb35df7d463205c411d51908e

Observation 5455eaff-064f-465d-a16a-3a90c0568d7e · outbound

This paper cites Modeling multisource multifrequency acoustic wavefields by a multiscale fourier feature physics-informed neural network with adaptive activation functions.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Modeling multisource multifrequency acoustic wavefields by a multiscale fourier feature physics-informed neural network with adaptive activation functions

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.560390Z digest=sha256:31d0b806a8dcd14f737ebe372d8d0feb0c67f0a1b20f36d3ca8eb6d138b6da32

Observation 0ae4e050-aac9-49dd-bb75-6d3c78f8b55b · outbound

This paper cites Solving the frequency-domain acoustic vti wave equation using physics-informed neural networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Solving the frequency-domain acoustic vti wave equation using physics-informed neural networks

Reference 22

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no resolver link, observed 2026-08-09T17:22:20.563331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.563331Z digest=sha256:7b1bdaf84422072b5bb48e993dca82067454cc74bd9f4facb270e697d7f011c7

Observation 54b9f998-c5a4-41c6-92ed-9f60be6d4830 · outbound

This paper cites A versatile framework to solve the helmholtz equation using physics-informed neural networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network A versatile framework to solve the helmholtz equation using physics-informed neural networks

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.737327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.566332Z digest=sha256:75e0a6e727c1c347bc314986c05c0c1865bc35a4f87fb4809ff969f37481138c

Observation 8cd9f776-7c6e-4538-9c41-b8051ebf7954 · outbound

This paper cites Pinneik: Eikonal solution using physics-informed neural networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Pinneik: Eikonal solution using physics-informed neural networks

Reference 24

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unresolved
no resolver link, observed 2026-08-09T17:22:20.569565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.569565Z digest=sha256:8356d59dc73794c1fc374383e4b9ec8069c00b4b083cc5bad63f73b66e4a53cf

Observation ad42d4cd-1ef4-43cd-a110-b3c542926a7b · outbound

This paper cites A modified physics-informed neural network with positional encoding.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network A modified physics-informed neural network with positional encoding

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.721222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.572825Z digest=sha256:7443a7565d305e03245ca4bea4cac927b917d6c55263d10f498e8ef9d9ebe281

Observation 2f68a750-1bd0-4e24-a26d-4fb752b2efff · outbound

This paper cites Helmholtz-equation solution in nonsmooth media by a physics-informed neural network incorporating quadratic terms and a perfectly matching layer condition.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Helmholtz-equation solution in nonsmooth media by a physics-informed neural network incorporating quadratic terms and a perfectly matching layer condition

Reference 26

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unresolved
no resolver link, observed 2026-08-09T17:22:20.575778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.575778Z digest=sha256:704a962f05dd30e03033282b9d9c5086c4aa5904f48a0173ac2387f854fae6d5

Observation d8b0f305-724c-4805-b11d-4b4ed546fa0d · outbound

This paper cites Physics-informed neural wavefields with gabor basis functions.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Physics-informed neural wavefields with gabor basis functions

Reference 27

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no resolver link, observed 2026-08-09T17:22:20.578799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.578799Z digest=sha256:4bcea453ed19c795ee545ddee56a3c77cd88a6780feae3e8e4a8e159e640632e

Observation 341d3cda-99ad-4d9d-aafd-6e6c90dd321f · outbound

This paper cites Meta-auto-decoder for solving parametric partial differential equations.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Meta-auto-decoder for solving parametric partial differential equations

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.699415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.581726Z digest=sha256:ba8dc5867da0d408cce73948dd0e0c7f04497c0b72e9fe6f4504cecd0bac6f75

Observation 4859a0c0-3316-4a94-8d3d-a2a71bff8909 · outbound

This paper cites Single reference frequency loss for multifrequency wavefield representation using physics-informed neural networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Single reference frequency loss for multifrequency wavefield representation using physics-informed neural networks

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.689764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.584666Z digest=sha256:02960e9d08cc649a0c20c6efa8c5f13c10b0884d8d40377c599444e109176bf6

Observation d8059ac1-dbe4-49ca-8e09-6234f2e780ae · outbound

This paper cites Simulating seismic multifrequency wavefields with the fourier feature physics-informed neural network.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Simulating seismic multifrequency wavefields with the fourier feature physics-informed neural network

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.679539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.587308Z digest=sha256:b13c0912377f52a943bba0bd4dc6e068314e649d3a6e1e22f21e0aafedfb51ba

Observation 431ce84d-fe7a-4e53-aaf6-9f2c669d2505 · outbound

This paper cites Multiple wavefield solutions in physics-informed neural networks using latent representation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Multiple wavefield solutions in physics-informed neural networks using latent representation

Reference 31

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unresolved
no resolver link, observed 2026-08-09T17:22:20.589874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:22:20.589874Z digest=sha256:7e3614209e422f21c099cf5c37fce89c6c1c5d3a289533af6f65e67691b20a77

Observation 7af66cd3-dae5-4f07-915f-8004fca935af · outbound

This paper cites Meta learning for improved neural network wavefield solutions.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Meta learning for improved neural network wavefield solutions

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T17:22:20.663101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T17:22:20.592314Z digest=sha256:419ff064c2a9152d08b585399d8d7de1b4156ff001b24257b2deab853fadee47

Observation 25d3e96e-13b9-41b8-8153-6df2637c777f · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Model-agnostic meta-learning for fast adaptation of deep networks

Reference 33

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unresolved
no resolver link, observed 2026-08-09T17:22:20.594863Z

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This paper cites Richards.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Richards

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This paper cites Wavefield solutions from machine learned functions constrained by the helmholtz equation.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Wavefield solutions from machine learned functions constrained by the helmholtz equation

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This paper cites Decoupled Weight Decay Regularization.

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network Decoupled Weight Decay Regularization

Reference 36

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Pith citing papers

Observation e2c3dce1-abcd-42ae-be27-fb8231029f91 · inbound

DiffPINN: Generative diffusion-initialized physics-informed neural networks for accelerating seismic wavefield representation cites this paper.

DiffPINN: Generative diffusion-initialized physics-informed neural networks for accelerating seismic wavefield representation Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network

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