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Paper Citation Record · LEDGER

MgNO: Efficient Parameterization of Linear Operators via Multigrid

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.19809.

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

pith.paper-citation-record.v1
2310.19809 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:31:52.999441Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T23:54:03.210702Z

Reference resolution

0 of 0 outbound references displayed

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

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5758ad22-d8ef-4e17-9da2-a299ee5f7811 · inbound

A deformation-based framework for learning solution mappings of PDEs defined on varying domains cites this paper.

A deformation-based framework for learning solution mappings of PDEs defined on varying domains MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T04:31:52.999441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:31:52.999441Z digest=sha256:92e3e23ac4375407d8dd3e5e5b1724964a613399a3db2cdbbb06ebdaf8f91db0

Observation 3fe13b72-14d5-4226-877d-9d4692dc5f54 · inbound

Point Cloud Neural Operator for Parametric PDEs on Complex and Variable Geometries cites this paper.

Point Cloud Neural Operator for Parametric PDEs on Complex and Variable Geometries MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 119

Resolution
unresolved
no resolver link, observed 2026-08-10T15:12:46.421957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:12:46.421957Z digest=sha256:b2878858e624dbb5ecc78b2743f52c8da590cbfc04ac25286dc395554da4fe4a

Observation 57b755ed-0649-4fb4-afa4-0ae86a1e05f5 · inbound

OpenBreastUS: Benchmarking Neural Operators for Wave Imaging Using Breast Ultrasound Computed Tomography cites this paper.

OpenBreastUS: Benchmarking Neural Operators for Wave Imaging Using Breast Ultrasound Computed Tomography MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:47:31.929982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:47:31.929982Z digest=sha256:5d40592f69b3c1f6f116f1bed445f02088752252d166d6a673d63fc706438b2e

Observation 3f0b3bfa-5fad-47a0-8bfd-9b2386b3220c · inbound

Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators cites this paper.

Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:12:02.564844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T04:07:42.061343Z digest=sha256:4e1ae836a81817882ba479a33f9c8355ed5515ac2cb160f35ad3ae82cc209b41

Observation 7ecdecf7-20d7-4484-b03e-7edaef06da3b · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:21:26.102589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-12T03:27:14.464987Z digest=sha256:f6b4ba1ceb6d09861caf1ead49253e2e0a44986d9057956b69a523dde6ff6345

Observation 8ad93a95-9b1d-4051-a261-ff52674a34b2 · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:22:59.064531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-14T21:21:32.256476Z digest=sha256:7149d4b4ffd7a8faa87b2e1b7e7ec4e8f2f05a7de1e543c85db7fa46c095854b

Observation eb0f203d-c38c-4d0e-a665-d844d127b76a · inbound

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts cites this paper.

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:08:29.764326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T02:03:50.528627Z digest=sha256:9a0441d9e6049804fd2253e34e4f24882abef37dbb9878a1d35383ee95996cd2

Observation 98e17488-88d7-4c4d-ac15-cae1776729a9 · 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 MgNO: Efficient Parameterization of Linear Operators via Multigrid

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:54:03.212163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-29T23:53:30.631124Z digest=sha256:9877e4ba4866fe91cfdd78efa86507e025c122e0ddacd1f91e97f946e0d70d15