Paper Citation Record · LEDGER

Understanding convolution on graphs via energies

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2206.10991.

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

pith.paper-citation-record.v1
2206.10991 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:05:12.857963Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T17:14:56.823672Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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 1c6d6caf-108c-4418-b375-cc083cc56ca5 · inbound

Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion cites this paper.

Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion Understanding convolution on graphs via energies

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T11:05:12.857963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30ef06ba-f79f-4ca9-9d40-6a58fd146348 · inbound

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows cites this paper.

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows Understanding convolution on graphs via energies

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T23:39:46.095588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5d9e79d-8e9e-40cc-b936-4750108cc355 · inbound

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors cites this paper.

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors Understanding convolution on graphs via energies

Reference 112

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:21:04.947198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6fa761f6-9d63-4195-887a-5c71908ca568 · inbound

Graph Navier Stokes Networks cites this paper.

Graph Navier Stokes Networks Understanding convolution on graphs via energies

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:13:58.221137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b91947c-be13-4bdc-8841-d87fc00a3236 · inbound

Graph Navier Stokes Networks cites this paper.

Graph Navier Stokes Networks Understanding convolution on graphs via energies

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:14:56.825088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b2993af-ed48-4524-90b9-1cc8a5af5447 · inbound

Learning Dynamic Stability Landscapes in Synchronization Networks cites this paper.

Learning Dynamic Stability Landscapes in Synchronization Networks Understanding convolution on graphs via energies

Reference 160

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:05:22.704024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 31d2cbe8-35b5-4ec7-a8cc-f93ccda6903e · inbound

Benchmarking Sheaf Neural Networks for Inductive Tasks cites this paper.

Benchmarking Sheaf Neural Networks for Inductive Tasks Understanding convolution on graphs via energies

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T04:52:31.771665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.