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Paper Citation Record · LEDGER

A posteriori analysis of neural network approximations

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2507.06017.

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

pith.paper-citation-record.v1
2507.06017 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:21:24.892199Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T15:56:53.406744Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:29:35.961875Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy26
  • unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4164db2c-4e2c-4993-ac5b-eeb98fd52bc6 · outbound

This paper cites Aurada, M.

A posteriori analysis of neural network approximations Aurada, M

Reference 1

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.746587Z digest=sha256:ef698e071c34b7841403cf5163154bd5593517f47f036c6b7ea1207aa84b6949

Observation 24e65089-3df6-4037-8cf1-b329f24e4591 · outbound

This paper cites Enforcing dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks.

A posteriori analysis of neural network approximations Enforcing dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dc1e9e12-9df4-4e7f-8a0c-bbacb6debcd7 · outbound

This paper cites Bochev and Max D.

A posteriori analysis of neural network approximations Bochev and Max D

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 34104b0e-995c-4556-9382-906186fa6356 · outbound

This paper cites Finite element interpolated neural networks for solving forward and inverse problems.

A posteriori analysis of neural network approximations Finite element interpolated neural networks for solving forward and inverse problems

Reference 4

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.760816Z digest=sha256:a7ec05ea0d0b9fc74af223fcebdc0b5f5683e0d2116e751f094998fd28009bc3

Observation 3b036cb3-892d-4615-847a-25339ffbb802 · outbound

This paper cites Numerical solution of inverse problems by weak adversarial networks.

A posteriori analysis of neural network approximations Numerical solution of inverse problems by weak adversarial networks

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9b3d3664-0012-409f-bbec-c949dd423804 · outbound

This paper cites Deep least-squares methods: An unsupervised learning-based numerical method for solving elliptic pdes.

A posteriori analysis of neural network approximations Deep least-squares methods: An unsupervised learning-based numerical method for solving elliptic pdes

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.770111Z digest=sha256:e70a9e5c83349bad391229ad8d628318842be456b558bb819f12d2affa32d5a2

Observation f07c2d21-0382-4717-998b-ae66f437cb66 · outbound

This paper cites A posteriori error control for DPG methods.

A posteriori analysis of neural network approximations A posteriori error control for DPG methods

Reference 7

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.775614Z digest=sha256:3d4d146a1d9326e0901cef2729feca3956d94275f234bc39114e8008e12e98b7

Observation 95a093e8-90ef-4a04-ab71-aacae7617e65 · outbound

This paper cites Carstensen, L.

A posteriori analysis of neural network approximations Carstensen, L

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7db17621-6b2e-426a-a410-d0b0fda5a791 · outbound

This paper cites Demkowicz and J.

A posteriori analysis of neural network approximations Demkowicz and J

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.785813Z digest=sha256:b65d1ef7a62e4d159fe1a7e606a43eb3061f71919b5eb0575929dbc201efad87

Observation 8306a96a-98ad-4b04-abfe-dfef82baf7c6 · outbound

This paper cites The discontinuous petrov–galerkin method.

A posteriori analysis of neural network approximations The discontinuous petrov–galerkin method

Reference 10

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.790152Z digest=sha256:b4ecf94d712888111a1deb72d59e039c1bd6b32c6b659d9d6c2d96ec8d5f5e57

Observation 84ee0571-628c-4a28-a154-4014fb93e057 · outbound

This paper cites Equivalence of local- and global-best approximations, a simple stable local commuting projector, and optimal hp approximation estimates in H( div ).

A posteriori analysis of neural network approximations Equivalence of local- and global-best approximations, a simple stable local commuting projector, and optimal hp approximation estimates in H( div )

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.794714Z digest=sha256:7418b930b5d5a9a2dc445819fb93a86197df2dce48885953fa6afdbc55b0f0c2

Observation 8df1ef56-a42e-4910-987b-5db616aabb9c · outbound

This paper cites A posteriori certification of PDE approximations with particular application to neural networks.

A posteriori analysis of neural network approximations A posteriori certification of PDE approximations with particular application to neural networks

Reference 12

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verified exact
local_arxiv, observed 2026-08-06T19:21:25.147061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3e858f29-ea35-48ca-bdd8-cda56c70786b · outbound

This paper cites Multilevel decompositions and norms for negative order S obolev spaces.

A posteriori analysis of neural network approximations Multilevel decompositions and norms for negative order S obolev spaces

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 2026-08-08T06:32:00.761636+00:00.

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Observation 7794e2f2-5fce-4c85-a6f6-0a7e58fe4525 · outbound

This paper cites Hiptmair.

A posteriori analysis of neural network approximations Hiptmair

Reference 14

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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 2026-08-08T06:32:00.761636+00:00.

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Observation 45f98d43-577f-45b9-9430-6840e2fc41e5 · outbound

This paper cites Characterizing possible failure modes in physics-informed neural networks.

A posteriori analysis of neural network approximations Characterizing possible failure modes in physics-informed neural networks

Reference 15

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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 2026-08-08T06:32:00.761636+00:00.

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Observation f2994b91-9ea1-458d-8558-1e606b8f61e3 · outbound

This paper cites Variational Physics-Informed Neural Networks For Solving Partial Differential Equations.

A posteriori analysis of neural network approximations Variational Physics-Informed Neural Networks For Solving Partial Differential Equations

Reference 16

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no resolver link, observed 2026-08-06T19:21:24.819465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:21:24.819465Z digest=sha256:b729059b5422b17f72807dc7444a65299193d9f90b5d267c63f0e9c908a6f75f

Observation d1003254-5e3b-4e0d-a7a3-05989069ef1d · outbound

This paper cites hp-vpinns: Variational physics-informed neural networks with domain decomposition.

A posteriori analysis of neural network approximations hp-vpinns: Variational physics-informed neural networks with domain decomposition

Reference 17

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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 2026-08-08T06:32:00.761636+00:00.

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Observation b127a9d7-7f6d-4886-ae9b-be4fefa38f62 · outbound

This paper cites Deep learning.

A posteriori analysis of neural network approximations Deep learning

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c03d861e-50d6-49f1-89ca-d890ab8a3b6a · outbound

This paper cites Paddy Disease Detection and Classification Using Computer Vision Techniques: A Mobile Application to Detect Paddy Disease.

A posteriori analysis of neural network approximations Paddy Disease Detection and Classification Using Computer Vision Techniques: A Mobile Application to Detect Paddy Disease

Reference 19

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local_arxiv, observed 2026-08-06T19:21:25.096409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.833864Z digest=sha256:069582fc926f4c6eb4f33d2de27526eec2b88d4493dd3ef0a8f005c797c85231

Observation 610b7bc9-9b75-4b30-a2b8-25d5fdaa7394 · outbound

This paper cites Minimal residual methods in negative or fractional S obolev norms.

A posteriori analysis of neural network approximations Minimal residual methods in negative or fractional S obolev norms

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fc5bc07e-0794-4852-beae-b4e423175ab6 · outbound

This paper cites Multilevel finite element approximation.

A posteriori analysis of neural network approximations Multilevel finite element approximation

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f9614e1b-3475-4771-ac10-e9f635fb0682 · outbound

This paper cites Robust variational physics-informed neural networks.

A posteriori analysis of neural network approximations Robust variational physics-informed neural networks

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.847667Z digest=sha256:280b21d952a601dd2beb1e6dae70d372eae73b4ad45283713b91706e78b173b7

Observation 7d395cae-d985-43ed-b5da-ad79d7cec98c · outbound

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

A posteriori analysis of neural network approximations Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 23

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unresolved
no resolver link, observed 2026-08-06T19:21:24.852521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:21:24.852521Z digest=sha256:5776612afbc5efa954266111adc2c2d984d3613113292fd9f49578bbeae5423d

Observation b980d9ab-b18c-410d-8232-fbcae136dc15 · outbound

This paper cites Stephan and Thanh Tran.

A posteriori analysis of neural network approximations Stephan and Thanh Tran

Reference 24

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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 2026-08-08T06:32:00.761636+00:00.

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Observation 74d0e47e-fb30-435c-9431-beaf484e8375 · outbound

This paper cites Uniform preconditioners for problems of negative order.

A posteriori analysis of neural network approximations Uniform preconditioners for problems of negative order

Reference 25

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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 2026-08-08T06:32:00.761636+00:00.

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Observation de5b71d1-1f0d-4047-adf3-02dc9940d7c5 · outbound

This paper cites Uniform preconditioners for problems of positive order.

A posteriori analysis of neural network approximations Uniform preconditioners for problems of positive order

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.865382Z digest=sha256:d2f21c3f3da5500f5c1b3397db57356d6ab58d53aa83d24ebf1b12d56d8a91f4

Observation b23fbc92-be0d-4893-a31c-d6a492c6b380 · outbound

This paper cites A deep fourier residual method for solving pdes using neural networks.

A posteriori analysis of neural network approximations A deep fourier residual method for solving pdes using neural networks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:21:25.243372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.869793Z digest=sha256:26133675d162c24ba17004960b08bb407faf3972e18926b71ac68caa64e2595b

Observation 26ee1b2b-cfc9-4445-a8cb-679eff371370 · outbound

This paper cites Optimizing variational physics-informed neural networks using least squares.

A posteriori analysis of neural network approximations Optimizing variational physics-informed neural networks using least squares

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:21:25.219589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f559c938-5c74-4d17-9c22-140eef2fc189 · outbound

This paper cites Neural network methods for power series problems of perron-frobenius operators.

A posteriori analysis of neural network approximations Neural network methods for power series problems of perron-frobenius operators

Reference 29

Resolution
verified exact
raw_fallback, observed 2026-08-06T19:21:25.071951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.879283Z digest=sha256:4eb9eba4c2e3ed0ec64f684043c55378af5c078bd50330c67e72cad4adf68615

Observation 8b557896-4ce4-4600-9774-f94c34a4b600 · outbound

This paper cites Verf\"urth.

A posteriori analysis of neural network approximations Verf\"urth

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T19:21:25.198417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.883563Z digest=sha256:d8b30f464a92c1839f5af32a517f00a61b0241331fa8f05b98afdfd3d01db706

Observation 34fd85d4-8e98-4240-9092-0d3213d8d194 · outbound

This paper cites When and why pinns fail to train: A neural tangent kernel perspective.

A posteriori analysis of neural network approximations When and why pinns fail to train: A neural tangent kernel perspective

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T19:21:24.887870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:21:24.887870Z digest=sha256:f4e6f26763f363bb26408dcc734f909ae376ba3c58be38ff46985aa0bfd4f4e1

Observation 247b1c16-6753-432a-899a-21ca6506fdc9 · outbound

This paper cites The deep ritz method: a deep learning-based numerical algorithm for solving variational problems.

A posteriori analysis of neural network approximations The deep ritz method: a deep learning-based numerical algorithm for solving variational problems

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:21:25.167055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T19:21:24.892199Z digest=sha256:e889552a204a00eed2b736eac8ff0904139ee3d1e41e7b0eb3cab78e97f96476

Pith citing papers

Observation 09785a76-fec8-432e-a3fd-9fa5ec9a6b3a · inbound

Neural network approximation in discrete dual norms with adaptive test spaces cites this paper.

Neural network approximation in discrete dual norms with adaptive test spaces A posteriori analysis of neural network approximations

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-04T05:29:35.963688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T15:56:53.406744Z digest=sha256:3c47d6d86c430c4396f64b20e82b95b3d487f80b364335039203e739d75f9d79