Paper Citation Record · LEDGER

Clifford Neural Layers for PDE Modeling

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2209.04934.

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

pith.paper-citation-record.v1
2209.04934 v2

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 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:14:46.318009Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T03:24:12.770033Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 6b0c720a-d403-4416-abff-3fdfc3b6d6e7 · 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 Clifford Neural Layers for PDE Modeling

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-24T09:39:17.290927Z

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 339458a6-d4ce-40fc-851b-9f8e9ea61308 · inbound

Representation Learning for Equivariant Inference with Guarantees cites this paper.

Representation Learning for Equivariant Inference with Guarantees Clifford Neural Layers for PDE Modeling

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:46.318009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f81454b7-e765-445c-9550-e6532424221e · inbound

Fast Clifford Neural Layers cites this paper.

Fast Clifford Neural Layers Clifford Neural Layers for PDE Modeling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:44.720682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf0a476f-e3b9-4487-ae21-ec5b986bee91 · inbound

Composing Linear Layers from Irreducibles cites this paper.

Composing Linear Layers from Irreducibles Clifford Neural Layers for PDE Modeling

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:48.308608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7901a0c-1040-4c85-9d84-5df30988107c · inbound

Modeling turbulent and self-gravitating fluids with Fourier neural operators cites this paper.

Modeling turbulent and self-gravitating fluids with Fourier neural operators Clifford Neural Layers for PDE Modeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T10:46:04.925998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5580ac2d-7b95-4b23-b21e-70f271f5c025 · inbound

Physics-informed sensor coverage through structure preserving machine learning cites this paper.

Physics-informed sensor coverage through structure preserving machine learning Clifford Neural Layers for PDE Modeling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T17:58:14.825172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ac3faae-9e2b-4143-b8fa-5eaaee61d8e8 · inbound

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs cites this paper.

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs Clifford Neural Layers for PDE Modeling

Reference 1988

Resolution: unresolved; no resolver link, observed 2026-08-03T05:22:10.855079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58343624-2618-4392-910e-8ad7e164aef9 · inbound

Geometric Algebra Meets Cartesian Tensors: Higher-Order Equivariance for Interatomic Potentials cites this paper.

Geometric Algebra Meets Cartesian Tensors: Higher-Order Equivariance for Interatomic Potentials Clifford Neural Layers for PDE Modeling

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T03:24:12.771417Z

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.