Paper Citation Record · LEDGER

Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.01074.

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

pith.paper-citation-record.v1
2210.01074 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:33:45.369483Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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External citation measurements

3
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3494f3be-bb4f-4ea1-9642-8e786c10b7c1 · inbound

Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations cites this paper.

Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-24T09:39:17.225740Z

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 4d201e86-6527-4a6b-b113-5cade8086012 · inbound

Neural Operators Can Play Dynamic Stackelberg Games cites this paper.

Neural Operators Can Play Dynamic Stackelberg Games Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.369483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f335edd-e935-4019-aeba-a7e2b6d4e461 · inbound

FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning cites this paper.

FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:06:35.144940Z

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 8ab733ef-c644-46f3-8a00-9e77d7ae596c · inbound

Smooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions cites this paper.

Smooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:08:06.386321Z

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 192f6e9c-b3b2-47ae-8745-72f5489b5278 · inbound

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients cites this paper.

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:54:03.190478Z

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 3e4cc35c-3702-4e9f-805d-8fa3ffbef748 · inbound

Inverse Low-Dimensional Manifold Reconstruction Framework for Spatiotemporal Reconstruction of Compressible Physical Fields cites this paper.

Inverse Low-Dimensional Manifold Reconstruction Framework for Spatiotemporal Reconstruction of Compressible Physical Fields Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-09T20:36:31.520397Z

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.