Paper Citation Record · LEDGER

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.21736.

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

pith.paper-citation-record.v1
2505.21736 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:34:09.062056Z

measured 32 of 32 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy13
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb5ddc3d-d920-422e-b468-43deb6c71377 · outbound

This paper cites Balakrishnan, A.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Balakrishnan, A

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:12.429030Z

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 6911c15c-33e4-471a-8d31-ec854939a5dc · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:12.314561Z

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 0c93943e-0e31-4708-a049-bdb81d16b5a4 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:12.173640Z

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 5b98c202-044d-45c7-9753-d194bedfd88f · outbound

This paper cites Bökman and F.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Bökman and F

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:12.033832Z

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 e44f4030-1c8f-43f5-9398-b0c7b16c4a13 · outbound

This paper cites Bruna and S.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Bruna and S

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:11.919740Z

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 c3f77137-1c31-4382-b209-e014819b6107 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:11.802990Z

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 8e8269e2-d77e-4f32-b4de-2880c661f1c5 · outbound

This paper cites Cohen and M.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Cohen and M

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:11.666307Z

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 ba5ed014-9573-4ace-803e-b294c97f69f9 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:11.536183Z

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 cf5163dc-24cf-4b9a-b0ff-14a1babf68f9 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:11.369905Z

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 26c4876d-a142-4cea-b0a5-ce5e9fe2d75a · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:11.244419Z

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 77256aaf-9264-4ee1-9502-4c3656ca2d78 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:06.967726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 422e8d6f-0d21-4049-a28b-701da081f364 · outbound

This paper cites Hoffmann, B.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Hoffmann, B

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:11.129658Z

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 d6f11edf-8226-4f9f-9431-86c138265ecd · outbound

This paper cites Ioffe and C.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Ioffe and C

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:07.136954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6f81336-ee92-4a6c-989f-063c75a90fde · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Adam: A Method for Stochastic Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:07.331919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ace9f10-94fd-4cc6-8480-10498ab2a648 · outbound

This paper cites Klein, J.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Klein, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.959663Z

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 2daabdfb-003f-4f3c-8f69-f08e7a08ebc7 · outbound

This paper cites Krizhevsky, I.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Krizhevsky, I

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:07.567291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6fb8815-a46e-4346-8411-551d3cb0767b · outbound

This paper cites A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:07.726923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcdca59a-1e25-4ddb-9138-52ce13023465 · outbound

This paper cites LeCun, B.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks LeCun, B

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.830251Z

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 52ce47d6-3721-4df6-8704-8bf81d3ee281 · outbound

This paper cites Matrix-valued Kernels for Shape Deformation Analysis.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Matrix-valued Kernels for Shape Deformation Analysis

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:34:09.268290Z

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 e2173562-1b93-4976-928b-21020e4155af · outbound

This paper cites Nishimaki, H.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Nishimaki, H

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.684867Z

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 6f91e29a-6257-4152-9fb8-3e8e7a6cb404 · outbound

This paper cites Pachitariu and C.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Pachitariu and C

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.516379Z

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 6b52ab2a-48b3-465f-ae4d-0c6ab8d04f80 · outbound

This paper cites Puglisi, D.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Puglisi, D

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.359435Z

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 b1ba4ce4-5758-40a5-ad90-75823babc78f · outbound

This paper cites Redmon, S.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Redmon, S

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:08.352036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 871bc22f-4a8e-4649-8711-74895b3d27cb · outbound

This paper cites Ronneberger, P.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Ronneberger, P

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:08.399061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fb857e0-8108-40ed-990a-9566d0bc251d · outbound

This paper cites Stringer, T.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Stringer, T

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:10.238021Z

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 19414204-1b0b-490e-af6b-e0e4aec2677b · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:08.564072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 819eb7cd-673d-45e3-92ee-09a28c395549 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:10.069411Z

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 ca4a2e0e-d7da-4a52-b95a-9234b216ae59 · outbound

This paper cites Weiler, M.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Weiler, M

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:09.932647Z

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 798a43ae-20db-41af-9e23-e8b2dde8cc55 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:09.774355Z

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 a5842c95-afd2-4a8b-a894-797247f6e06d · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:34:08.905713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf32d644-07b8-4889-bb4c-c9bdca7527f8 · outbound

This paper cites an unresolved cited work.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:34:09.550225Z

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 356e7bbc-3735-43f5-8710-e6367f8325bb · outbound

This paper cites A first moment kernel.

Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks A first moment kernel

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:34:09.409853Z

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.

Pith citing papers

No inbound Pith citation observations are available.