Paper Citation Record · LEDGER

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2003.05425.

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

pith.paper-citation-record.v1
2003.05425 v3

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 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:11:41.659284Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T08:59:55.462547Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 ff43acea-cec6-42d2-ace6-87bfd7ce9a13 · inbound

Geometric Hyena Networks for Large-scale Equivariant Learning cites this paper.

Geometric Hyena Networks for Large-scale Equivariant Learning Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:41.659284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d014ebd2-2f13-4493-b03b-7d6affef0426 · inbound

Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces cites this paper.

Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:09:46.144332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 398d14a8-a43f-48c6-be5c-7db3c003cff9 · inbound

Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves cites this paper.

Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:01:19.090661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aae06787-1671-46be-b473-e64f01b3044c · inbound

Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves cites this paper.

Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:59:55.464530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a6aa6bc7-5f2b-4be9-823f-abaa3759c6de · inbound

Augmented Equivariant Mesh Networks for Anatomical Segmentation cites this paper.

Augmented Equivariant Mesh Networks for Anatomical Segmentation Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:01:27.770357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 421444e9-2374-4d9e-9d4b-8a9a2611c768 · inbound

Intrinsic and Triangulation-Agnostic Attention: A Simple and Powerful Approach for Learning on Meshes cites this paper.

Intrinsic and Triangulation-Agnostic Attention: A Simple and Powerful Approach for Learning on Meshes Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T05:06:54.931417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.