Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MgNO: Efficient Parameterization of Linear Operators via Multigrid
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2310.19809.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:29:14.330942Z
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
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- parse uncertain0
- malformed identifier0
- metadata mismatch0
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 51844214-c8e7-4855-985e-e7c6642d1fa4 · inbound
Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries cites this paper.
Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries MgNO: Efficient Parameterization of Linear Operators via Multigrid
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:29:14.330942Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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.
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.
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.
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 2026-08-14T06:32:32.682623+00:00.
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 2026-08-14T06:32:32.682623+00:00.
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 2026-08-14T06:32:32.682623+00:00.
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 2026-08-14T06:32:32.682623+00:00.
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 2026-08-14T06:32:32.682623+00:00.