Paper Citation Record · LEDGER

Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2106.06020.

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

pith.paper-citation-record.v1
2106.06020 v1

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 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:36:20.092279Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:45:05.602738Z

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 27703891-0a63-45e2-9e77-d917b04e13bd · inbound

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing cites this paper.

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T15:36:20.092279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31e45e18-385e-4686-9d44-5a623ba5eb4e · inbound

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks cites this paper.

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:46:23.359865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 979d806f-5fd8-41d3-9e78-10464ef35bf3 · inbound

Towards a Multi-Embodied Grasping Agent cites this paper.

Towards a Multi-Embodied Grasping Agent Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T03:05:48.216790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f514b08d-764e-4dd4-8a65-a3cacb2917a8 · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:07:51.574530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e5dd2ff-252c-4e18-8f16-983ee4cc36be · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T21:45:05.604398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 568bfdba-73b1-4168-a412-17a98a27ccfd · inbound

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space cites this paper.

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-19T15:57:49.391646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.