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Paper Citation Record · LEDGER

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks

As of 19 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2508.00267.

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

pith.paper-citation-record.v1
2508.00267 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:19:10.316909Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

62 of 62 outbound references displayed

  • verified exact4
  • verified fuzzy40
  • unresolved17
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4bcfd90b-ad9a-49ec-acc5-e6b90e39bab1 · outbound

This paper cites Stochastic Training of Graph Convolutional Networks with Variance Reduction.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Stochastic Training of Graph Convolutional Networks with Variance Reduction

Reference 1

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source=arxiv_source observed=2026-08-06T10:19:01.590669Z digest=sha256:e3f99d4b9ab5fb843c171ebde466fe5f7dd8cce382e0400bfaa25c7e79511824

Observation 252fdf2d-16d4-4f4a-ad7e-7f6114faa610 · outbound

This paper cites , Wang , Y.-C.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Y.-C

Reference 2

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Observation a4b43d47-21cd-4b82-abda-d306cf278f6c · outbound

This paper cites , Ma , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ma , Y

Reference 3

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Observation db929f32-b919-4e7b-b188-0d2c8315b38b · outbound

This paper cites , Lee , Y.-C.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lee , Y.-C

Reference 4

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source=arxiv_source observed=2026-08-06T10:19:01.971086Z digest=sha256:615822e392ca4dda6ffab637ea20f963d128f93e997219c3748d6d2e8d07dc8c

Observation 236604e3-76ec-4238-879e-028f94f6a132 · outbound

This paper cites , Sanchez-Gonzalez , A.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Sanchez-Gonzalez , A

Reference 5

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source=arxiv_source observed=2026-08-06T10:19:02.085500Z digest=sha256:0e2006b277c34e26ef0de27fcb1e88adfe12b2ca38eed0f7c2cbca2f02c50fbc

Observation 340ae92b-32ac-46de-8acf-6e13a297f358 · outbound

This paper cites , Schoenholz , S.S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Schoenholz , S.S

Reference 6

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Observation 7cb3e6c4-bc4a-448d-b65e-60d2eb8bd557 · outbound

This paper cites , Zeng , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zeng , J

Reference 7

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source=arxiv_source observed=2026-08-06T10:19:02.390431Z digest=sha256:140d3358769cbe02866b360a7dcb3b84302a0ef871a31d76c6997e28e96f8254

Observation 3da2d566-a3b0-4c39-85e9-e2ecb200370c · outbound

This paper cites , Monfardini , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monfardini , G

Reference 8

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source=arxiv_source observed=2026-08-06T10:19:02.517761Z digest=sha256:a3fa7b089928d481242756d4e499178d07164b163390958ce5e69718b18b0a1f

Observation c6c7c669-e381-49e5-a369-27c2e9df17c1 · outbound

This paper cites , Gori , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Gori , M

Reference 9

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source=arxiv_source observed=2026-08-06T10:19:02.646829Z digest=sha256:d5d4b746b646531153054e22b5b1c09cefdc24d0d93be29c5709af73cd94ab68

Observation d51cf396-2b42-4188-911e-91bf68c9b168 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 10

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source=arxiv_source observed=2026-08-06T10:19:02.769657Z digest=sha256:b2e354ad4a1c8a1273573bc92456349b2089196b1e4a37b164ad784d39535a8d

Observation 31b9ad19-c345-4493-afc9-8bb460624566 · outbound

This paper cites DeeperGCN: All You Need to Train Deeper GCNs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks DeeperGCN: All You Need to Train Deeper GCNs

Reference 11

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source=arxiv_source observed=2026-08-06T10:19:02.881461Z digest=sha256:f9da01bc08993baf27faf0caa56e48635d8b13e8176d942f0e82b911038663a7

Observation ad500c2c-cbad-4cf3-8e1f-72e2905ecbf9 · outbound

This paper cites , Yang , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yang , J

Reference 12

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source=arxiv_source observed=2026-08-06T10:19:03.069375Z digest=sha256:af291596a2bc4bf63a4f81491919c12d671c3797474b6b8ae27e10ac1e5505f6

Observation efa9c0c7-b421-4bc2-948e-dd27c3c0d23d · outbound

This paper cites , Ying , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ying , Z

Reference 13

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source=arxiv_source observed=2026-08-06T10:19:03.186426Z digest=sha256:3e48d2eab0affa6324e98c6c78b354d66691705e78c49342683c6fcb7e6f49dc

Observation d610a253-a09c-44a7-aa42-0935ee6c2518 · outbound

This paper cites FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

Reference 14

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Observation 59510a0f-e7e3-48c3-95d5-a20c00bdc9e3 · outbound

This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 15

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source=arxiv_source observed=2026-08-06T10:19:03.413357Z digest=sha256:048e3751d4db89d336a8ccc69e65ae5cae9200713487227cb759e36441896917

Observation e0e0513c-c0c1-4364-91d4-ea772dec987e · outbound

This paper cites , M \"u ller , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , M \"u ller , M

Reference 16

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:03.579803Z digest=sha256:e33ed6123863dd9fad9325bef39eea158c2497008ed9a594896a91828a07bc3b

Observation f6bb27f3-68a0-4c73-97f8-14b7cf804abf · outbound

This paper cites , Monro , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monro , S

Reference 17

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source=arxiv_source observed=2026-08-06T10:19:03.708419Z digest=sha256:5d45329bd14758128dbe857ee6c1cd1f0926e41dbc48dc762ca879963b159ac2

Observation 841d0c9c-37a4-4562-ad81-cda072a29d2a · outbound

This paper cites : Introductory lectures on convex optimization - a basic course.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks : Introductory lectures on convex optimization - a basic course

Reference 18

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source=arxiv_source observed=2026-08-06T10:19:03.873509Z digest=sha256:4c75c82baf584142074a8dc2c48bfb944fb150c993b6b13029bb7a89fb4c4f82

Observation 20a37e67-0495-41b1-9900-b3df9f58aab4 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Adam: A Method for Stochastic Optimization

Reference 19

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Observation 489df2bc-1e1d-4f7e-848e-a6dbfa95e050 · outbound

This paper cites , Xu , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Xu , Y

Reference 20

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Observation a947c109-700c-46cc-a4e3-462c49abd0a2 · outbound

This paper cites : Some methods of speeding up the convergence of iteration methods.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks : Some methods of speeding up the convergence of iteration methods

Reference 21

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source=arxiv_source observed=2026-08-06T10:19:04.258032Z digest=sha256:f0f3ea2e0e1402d66dea6bd06c919cf0f8c208b858137c8ff8a8fbceb6716ff8

Observation ba49fd55-b695-4bb5-acc0-057b5baba4bf · outbound

This paper cites On the Convergence of Adam and Beyond.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of Adam and Beyond

Reference 22

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Observation e48acaeb-6fd9-4fc8-83e7-6ecec0fb9a02 · outbound

This paper cites , Hazan , E.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Hazan , E

Reference 23

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source=arxiv_source observed=2026-08-06T10:19:04.575581Z digest=sha256:6a1cdfabfc1d36d0626a9a8b0a6d16b2817b176a24b8beaa2d5a420823718064

Observation 4cde7304-9e3f-4584-befc-dfa5ff692a0b · outbound

This paper cites On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Reference 24

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source=arxiv_source observed=2026-08-06T10:19:04.740760Z digest=sha256:fedd2242112f7742bec6f367fe8de27a5b4c7408a9a6f73c75a0107f34e57080

Observation eeb6df83-598a-49f4-afe3-a1b022ba2b7b · outbound

This paper cites Gated Graph Sequence Neural Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Gated Graph Sequence Neural Networks

Reference 25

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Observation 5c439ebf-b98c-47fc-a37b-59a00b3f550b · outbound

This paper cites , Micheli , A.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Micheli , A

Reference 26

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Observation abf12a0b-c2ba-4bc6-ba84-4b1d53cabf8e · outbound

This paper cites , Kozareva , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Kozareva , Z

Reference 27

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source=arxiv_source observed=2026-08-06T10:19:05.210684Z digest=sha256:9a91b9aad92c2e4fd538975f170fff92202e6e4798df53b254cfcb77ea28f937

Observation c58e829b-37fa-4aef-beb7-6001979b3d52 · outbound

This paper cites , Pan , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Pan , S

Reference 28

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source=arxiv_source observed=2026-08-06T10:19:05.391697Z digest=sha256:81fb1f7d6fe3f056989c52fe62ede4f11f5b9961415b6e5f767195c496dfd76b

Observation 05e82857-b165-4119-8b59-6245ba46e15e · outbound

This paper cites Spectral Networks and Locally Connected Networks on Graphs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Spectral Networks and Locally Connected Networks on Graphs

Reference 29

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source=arxiv_source observed=2026-08-06T10:19:05.537427Z digest=sha256:0fae48fb00190b7c017185cff7722890e0a3b709ae9d05d4c865eb1dbd7a98f3

Observation 6e299552-f47b-4359-8eaa-f1c8a5c28457 · outbound

This paper cites Deep Convolutional Networks on Graph-Structured Data.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Deep Convolutional Networks on Graph-Structured Data

Reference 30

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source=arxiv_source observed=2026-08-06T10:19:05.710102Z digest=sha256:284f24f273f10766e2e25fa730588b98ff8277636c0fd3c1de2d6a05d13c4985

Observation d89a65a8-53ed-45ba-8128-8f8cb76e35c3 · outbound

This paper cites , Bresson , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Bresson , X

Reference 31

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source=arxiv_source observed=2026-08-06T10:19:05.844054Z digest=sha256:6c21b991e66ee5497f42e9b8837f56f56d701cc6ba53d866628af43f746d411a

Observation 518591de-8ec4-47f3-9f5c-86a92b6f9661 · outbound

This paper cites , Monti , F.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monti , F

Reference 32

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source=arxiv_source observed=2026-08-06T10:19:05.977147Z digest=sha256:327722aed78124ba48772ca24df0ac3fc84fdc35b80a5ee35b0ccd3e4dc6d485

Observation bbe0a83a-81f9-4185-bcbf-0b875e2ec0ef · outbound

This paper cites , Wang , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , S

Reference 33

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source=arxiv_source observed=2026-08-06T10:19:06.113429Z digest=sha256:162088fd2ae444da2c68a596bc9405f106b2f1addba09941f0e6a16a52391cf6

Observation 461ac51f-3a28-4916-b49c-f7ce14e73e56 · outbound

This paper cites , Ma , Q.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ma , Q

Reference 34

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Observation ebb7f712-12ad-45de-adb4-fd45063bb209 · outbound

This paper cites , Wang , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Z

Reference 35

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source=arxiv_source observed=2026-08-06T10:19:06.395396Z digest=sha256:d9ee52e2ae5d5d397f50fe69a6f7db27e4b6c2447c25533a3454e256d88de3d8

Observation 6fa451fb-671e-4ba8-be68-53fd4dcedd91 · outbound

This paper cites , Hu , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Hu , Z

Reference 36

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.533122Z digest=sha256:e232ff732abcda76ff779a20da2506a7c971ad390834ccdcf4790418098ac190

Observation cf7640ac-7fb8-40cd-be49-db8faefa5304 · outbound

This paper cites MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks

Reference 37

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local_arxiv, observed 2026-08-06T10:19:11.484007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.672858Z digest=sha256:f9e2c3f726f3532ca0021c49e50cac91edd8f6a0ff974f12109cbe41abd0728f

Observation d1d0d86a-0ef3-40f2-8417-1d0ee0693f47 · outbound

This paper cites , Zhang , T.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zhang , T

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.645420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.798233Z digest=sha256:1e00771150c441adf5af076a4db080e2c6ed20538893e9f2060fd54076fbf4c7

Observation a4df1047-bcfc-4408-8717-daadb4745aac · outbound

This paper cites , Liu , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Liu , X

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.346219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.894270Z digest=sha256:8834bb8f9ce6b0e02e82056ee6f1af53a090df9261f27ef97e69bc6be5910bc4

Observation 1e4509c3-e62e-41d2-ae4c-31ef655a7a3e · outbound

This paper cites PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:11.232422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.996256Z digest=sha256:7b0f0d9963214b83294a3f2b8a575396315ac7aa9e748307f45ef3de2f182a1b

Observation 67512972-91e1-4a67-913c-87434b44ce29 · outbound

This paper cites , Yang , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yang , X

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.056402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.090435Z digest=sha256:d7828a345ad86bb359f599560aff1e8e248f446ad1ae0da7ed602f1c0195397b

Observation 0b46f53e-f604-4ed0-98cd-9f24ae0f792e · outbound

This paper cites , Wang , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Y

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.764133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.201832Z digest=sha256:3db190bfbd1789e0722399ca746c7660a094d1b10aea1e7892138fd98b2bf907

Observation fc67b2de-5cdd-4f80-8662-75501ade45cb · outbound

This paper cites Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:10.945843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.354078Z digest=sha256:77bd0aec13706ab6f2d34e56b2889d71142f0c19771ae1e2a76ff6de2b9ca4c8

Observation ca11c649-9e81-405a-80c2-e4175671381d · outbound

This paper cites GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:10.616111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.491084Z digest=sha256:852ccc1f443da4228d750ef1432710ff3ccf46a0e7c4f64a75fdb5c14bf8c47b

Observation 13148f3f-bdc0-4096-867a-a38e6bd1cb5e · outbound

This paper cites , Liu , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Liu , G

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.493312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.625585Z digest=sha256:a25a9ac724be042428365700f1b4f816b8e8dd5a1657c046bbcda2cc8782a184

Observation a48b209e-c4bf-4a62-bb3b-7e24fa4b8683 · outbound

This paper cites , Lu , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lu , J

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.249183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.746062Z digest=sha256:ba414c8d741f400745b0ead7317d29039ecdabbfc3368659c1a346843de9bbd5

Observation 90898b8b-d007-4c76-b134-2e6b5ef0ec03 · outbound

This paper cites , Ramezani , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ramezani , M

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.879213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.854033Z digest=sha256:42506c57cacc90b04af5aae458eb304e65e0b4838b3b63231ffc3c2a9ac9bea1

Observation e0fb7412-1d38-4a21-8d6e-8e1c8d8b4f26 · outbound

This paper cites , Lou , H.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lou , H

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.579781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.017962Z digest=sha256:1f8ba9fbaf6be9d726e415128d147c1f2efe20ecabb3c3af98e53d36fc8bcebc

Observation b405db17-5e51-494a-a9ff-ab175dcc2263 · outbound

This paper cites , Feng , T.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Feng , T

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.253430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.221759Z digest=sha256:5db10af79ae6d2d41a083b61d51581b454a9d886ec242bb51d0b2ea84bc0ad05

Observation b71e5307-a8e5-48c4-9c24-31f728119e32 · outbound

This paper cites , Zhang , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zhang , Y

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.011437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.387857Z digest=sha256:a4beb1fcc4f59d01bc2a9f161f4eaa45dc0669d9e9e1560e6dc6b31e0098dfba

Observation 40e8d92f-dbc3-4b9d-8a5c-2b393e86b439 · outbound

This paper cites , Khalid , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Khalid , M

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.725724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.592394Z digest=sha256:569287ad4bf8f49f13c2460f96ca52b2cba4fc380ec12e1b666cf8ece4dbbdcc

Observation ffc7a728-ab2a-4a0b-9ca4-283d6bb6c096 · outbound

This paper cites , Zheng , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zheng , Z

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.471330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.679844Z digest=sha256:5d008a575b5642aa7307408b403089e39674580d0c1f9776d85c08808b755df0

Observation 67f6aa36-8aab-41fc-bc17-6767fa0759bb · outbound

This paper cites On the Convergence of SGD with Biased Gradients.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of SGD with Biased Gradients

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:08.874670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:08.874670Z digest=sha256:ec049d1bdf3f49929c41a15e791b5a9f208abaacec1d4ef2304df9629a812b69

Observation d98c7f71-0963-4958-93af-3844bbb969a1 · outbound

This paper cites , Yin , W.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yin , W

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.111712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.020753Z digest=sha256:4b3d05e125db06fe7b278c3df9ba8396908d63b5940005274275dab98a0b52bb

Observation 50dab936-8d95-4c99-9dcf-34ae6c451f7f · outbound

This paper cites , Carmon , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Carmon , Y

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.844610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.187227Z digest=sha256:e23d6a5039f1e20172602d0af030f4be642592beb710659daa7b4d72adaf9b35

Observation fe5adee0-5a5e-4015-8467-f5ed6f51eaef · outbound

This paper cites CogDL: A Comprehensive Library for Graph Deep Learning.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks CogDL: A Comprehensive Library for Graph Deep Learning

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:09.330652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:09.330652Z digest=sha256:b6f84cc743da875851b5312c4fd819552868a7ef279982b70da6f367fbf737ab

Observation 5bd4fdb6-d753-4e95-b83c-a2e071fbf7e1 · outbound

This paper cites , Gross , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Gross , S

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.563383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.430549Z digest=sha256:82cb0d87ebc3a828d8106add419f064520edf6afd296d4ce455aa2ff2a97f9c1

Observation bda93e3b-10bd-4aab-9694-2ccf27486825 · outbound

This paper cites , Namata , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Namata , G

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.258512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.613186Z digest=sha256:7c1f16ca9ff6c510dfb0351e39f716d3cb3c1aff9d8e8b0ec4c927d60e16e2d5

Observation 2deb5a45-893a-4a00-bd25-5d24e7b670c0 · outbound

This paper cites , Fey , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Fey , M

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:11.967081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.763685Z digest=sha256:eeba183a1dfe3382da1e839bced96fa7bf1631524e44f30bfc1f8bd15d9d2d12

Observation 09d5c99e-9238-466f-bac0-07485114f5f0 · outbound

This paper cites sn-basic.bst.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks sn-basic.bst

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:09.925497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:09.925497Z digest=sha256:122444cb6c551e10aacba1f82bf9b0d0eb4f145e9a8dd5e3d6e7deb69bea295a

Observation bfd5ca5b-7f57-4fff-8907-8cf241658dcc · outbound

This paper cites write newline.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks write newline

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:10.096506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:10.096506Z digest=sha256:a7a7d107af2873d1d723c28ddc34564cf50b4c143d1da3e05adb5a1c79d010f3

Observation accc6c32-a423-4330-b0e3-9e5be827d245 · outbound

This paper cites write newline.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks write newline

Reference 62

Resolution
malformed identifier
no resolver link, observed 2026-08-06T10:19:10.316909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:10.316909Z digest=sha256:7d0da44cb3a1163fcde5450b2697da0e095d69014b25fbebe45ad1f3863bd4cc

Pith citing papers

No inbound Pith citation observations are available.