Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T23:08:13.285717Z
Paper Citation Record · LEDGER
Graph Neural Networks Are Not Continuous Across Graph Resolutions
As of 9 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 1 inbound Pith citation observation for arXiv:2605.31315.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T01:52:01.332001Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
72 of 72 outbound references displayed
- verified exact20
- verified fuzzy0
- unresolved47
- parse uncertain0
- malformed identifier1
- metadata mismatch4
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 11b6ddb4-4680-4cb9-878e-a1fa6bda433f · outbound
This paper cites @esa (Ref.
Graph Neural Networks Are Not Continuous Across Graph Resolutions @esa (Ref
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44e781f5-08da-40bb-bb7b-adb6883e94aa · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 2
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00c8708b-3668-40d0-abb9-455645491c09 · outbound
This paper cites 1.0" encoding=.
Graph Neural Networks Are Not Continuous Across Graph Resolutions 1.0" encoding=
Reference 3
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32a71fad-1706-47aa-b5bc-4711a2dc4999 · outbound
This paper cites write newline.
Graph Neural Networks Are Not Continuous Across Graph Resolutions write newline
Reference 4
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00f2a0de-eb2c-4a0f-ab9b-cd3bd374b4dd · outbound
This paper cites Sharp davies--gaffney--grigor’yan lemma on graphs.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Sharp davies--gaffney--grigor’yan lemma on graphs
Reference 5
- Resolution
- verified exact
- doi, observed 2026-06-28T23:12:46.240507Z
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 376313f2-0098-4c69-af8d-c2036cf5fa3a · outbound
This paper cites M., Grattarola, D., Livi, L.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., Grattarola, D., Livi, L
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f05b506-c517-416a-8504-5eaa2598dd23 · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7878903-2aa0-4bd4-be72-925476472114 · outbound
This paper cites How attentive are graph attention networks? In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022.
Graph Neural Networks Are Not Continuous Across Graph Resolutions How attentive are graph attention networks? In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022
Reference 8
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 453c2a1c-9fb7-4289-9cb0-7da757cda4bb · outbound
This paper cites M., Bruna, J., Cohen, T., and Veličković, P.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., Bruna, J., Cohen, T., and Veličković, P
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87532e35-4fff-47f7-8473-8b0930174f61 · outbound
This paper cites Spectral networks and locally connected networks on graphs.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Spectral networks and locally connected networks on graphs
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f27200e8-e323-42a8-a233-9625e97105ed · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f25484c-9b83-4bef-ba6c-910e82cf2bfd · outbound
This paper cites Convolutional neural networks on graphs with fast localized spectral filtering.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Convolutional neural networks on graphs with fast localized spectral filtering
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e736495-dab3-4dc7-b9eb-22c1aa27fd72 · outbound
This paper cites and Lenssen, J.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Lenssen, J
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b775c246-17fb-4d23-a7e6-27702b45569d · outbound
This paper cites PyG 2.0: Scalable Learning on Real World Graphs.
Graph Neural Networks Are Not Continuous Across Graph Resolutions PyG 2.0: Scalable Learning on Real World Graphs
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.041449Z
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 8f8d6b57-e601-4158-a70c-081706eb13a2 · outbound
This paper cites Diffusion scattering transforms on graphs.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Diffusion scattering transforms on graphs
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28612a4f-cf77-4d38-aedc-b805334f5edd · outbound
This paper cites Stability properties of graph neural networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Stability properties of graph neural networks
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:46.236945Z
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 191f6ead-2fda-44f0-8fa2-2f2092a079fe · outbound
This paper cites Predict then propagate: Graph neural networks meet personalized pagerank.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Predict then propagate: Graph neural networks meet personalized pagerank
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a5fb05e-375f-423c-9ec4-f2d5ace0eb6c · outbound
This paper cites S., Riley, P.
Graph Neural Networks Are Not Continuous Across Graph Resolutions S., Riley, P
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4602ddad-4ef2-4e03-b5c4-45ca5069b179 · outbound
This paper cites L., Ying, Z., and Leskovec, J.
Graph Neural Networks Are Not Continuous Across Graph Resolutions L., Ying, Z., and Leskovec, J
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a9de0717-5212-440d-8bf5-6bcd0ba92324 · outbound
This paper cites Bernnet: Learning arbitrary graph spectral filters via bernstein approximation.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Bernnet: Learning arbitrary graph spectral filters via bernstein approximation
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a40b411d-43b4-4f43-901d-7976fd54ac53 · outbound
This paper cites Convolutional neural networks on graphs with chebyshev approximation, revisited.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Convolutional neural networks on graphs with chebyshev approximation, revisited
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c034d143-24bf-4021-8023-2dcfe8f207d7 · outbound
This paper cites Graph laplacians and their convergence on random neighborhood graphs.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Graph laplacians and their convergence on random neighborhood graphs
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c123f9c-5981-480d-b4d5-9f33b3d918f0 · outbound
This paper cites Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt
Reference 23
- Resolution
- verified exact
- doi, observed 2026-06-28T23:12:46.239533Z
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 dd2eb9d8-b4e9-4329-b341-3567da65be8d · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 24
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b9b0edf-4718-45b6-8989-fb49c41f86c4 · outbound
This paper cites Strategies for Pre-training Graph Neural Networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Strategies for Pre-training Graph Neural Networks
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:46.249084Z
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 172f3cc3-1f4f-40a1-a9e1-2d089c6bdef7 · outbound
This paper cites Highly accurate protein structure prediction with alphafold.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Highly accurate protein structure prediction with alphafold
Reference 26
- Resolution
- verified exact
- doi, observed 2026-06-28T23:12:46.246287Z
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 6bfe8944-16ec-46ed-83f7-46bf7c5336dc · outbound
This paper cites Perturbation theory for linear operators; 2nd ed.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Perturbation theory for linear operators; 2nd ed
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c331dacc-c180-485e-828f-00222bb3c1cb · outbound
This paper cites On the stability of graph convolutional neural networks under edge rewiring.
Graph Neural Networks Are Not Continuous Across Graph Resolutions On the stability of graph convolutional neural networks under edge rewiring
Reference 28
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a62a9db-d80f-4fe1-9fd9-ce408a028556 · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 29
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28e58eab-04bc-4675-9be5-20f63bb9bd5c · outbound
This paper cites Limitless stability for graph convolutional networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Limitless stability for graph convolutional networks
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ab13fa7-8c35-411c-baa2-6c31639d13ed · outbound
This paper cites Large coupling convergence beyond definiteness.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Large coupling convergence beyond definiteness
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.043613Z
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 1f8253a4-15c5-4cdd-b605-4a2c83e59bea · outbound
This paper cites Di-graphs with tightly connected clusters: effective graph laplacians and resolvent convergence.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Di-graphs with tightly connected clusters: effective graph laplacians and resolvent convergence
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.036110Z
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 249ce1d5-17ff-49e7-9426-dbb1caf493cc · outbound
This paper cites and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Cremers, D
Reference 33
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 558248c7-a33c-44f1-9993-6d04b217dced · outbound
This paper cites and Kutyniok, G.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Kutyniok, G
Reference 34
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a47c61de-2033-42e3-8f75-ba4563fe8f7f · outbound
This paper cites Resolvnet: A graph convolutional network with multi-scale consistency.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Resolvnet: A graph convolutional network with multi-scale consistency
Reference 35
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd5354f8-855d-4917-9769-7dac774d5097 · outbound
This paper cites M., and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., and Cremers, D
Reference 36
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb9e9dd5-ccb7-4a5f-a7f3-29f9d74b1324 · outbound
This paper cites M., and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., and Cremers, D
Reference 37
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b3d0f18-87d4-4aac-9839-f15b1700b9d9 · outbound
This paper cites M., and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., and Cremers, D
Reference 38
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46d2f50f-b135-4039-90d0-175cfdd7604e · outbound
This paper cites M., and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., and Cremers, D
Reference 39
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 127cd2a9-4da1-4ef2-b2ed-d02829195f73 · outbound
This paper cites M., and Cremers, D.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., and Cremers, D
Reference 40
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e6de59f-cefa-4794-8c00-16659de7cf8d · outbound
This paper cites doi: 10.1126/science.adi2336.
Graph Neural Networks Are Not Continuous Across Graph Resolutions doi: 10.1126/science.adi2336
Reference 41
- Resolution
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- doi, observed 2026-06-28T23:12:46.257537Z
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 aec3073d-9d12-449a-b940-f7336fef080f · outbound
This paper cites and Jegelka, S.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Jegelka, S
Reference 42
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c8d1df0-ea97-4021-98ba-2fabc121270f · outbound
This paper cites Self-attention graph pooling.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Self-attention graph pooling
Reference 43
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f8b86280-3011-4e30-bd70-cce225e74af1 · outbound
This paper cites Transferability of Spectral Graph Convolutional Neural Networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Transferability of Spectral Graph Convolutional Neural Networks
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.038883Z
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 e783d207-00a6-40b5-be83-06c702d94b55 · outbound
This paper cites On the Transferability of Spectral Graph Filters.
Graph Neural Networks Are Not Continuous Across Graph Resolutions On the Transferability of Spectral Graph Filters
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T23:12:47.036157Z
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 eeada14d-a695-4cb5-bde5-3a9779e58290 · outbound
This paper cites Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:46.253565Z
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 08d815c3-98a7-4d17-9ab7-d44fd7fc51fd · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07cafa44-df1b-47ef-8795-bfb7465cfa10 · outbound
This paper cites Graph reduction with spectral and cut guarantees.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Graph reduction with spectral and cut guarantees
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 814ba28a-8a0d-49d1-93b4-7357bd8ccf06 · outbound
This paper cites and Vandergheynst, P.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Vandergheynst, P
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 35bd3fc8-ab13-42de-842a-8e25712338ac · outbound
This paper cites and Vandergheynst, P.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Vandergheynst, P
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36bc642b-25ce-42ef-97c4-6f6e8b413bd6 · outbound
This paper cites Communications on Pure and Applied Mathematics , volume =.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Communications on Pure and Applied Mathematics , volume =
Reference 51
- Resolution
- metadata mismatch
- doi, observed 2026-06-28T23:12:46.244900Z
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 cef674fe-4549-4656-83b4-1dbeb2b69288 · outbound
This paper cites Transferability of Graph Neural Networks: an Extended Graphon Approach.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Transferability of Graph Neural Networks: an Extended Graphon Approach
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.046068Z
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 4ba82e24-f298-40b8-b922-50aff5e19169 · outbound
This paper cites Information Retrieval3(2), 127–163 (2000) https://doi.org/10.1023/A:1009953814988.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Information Retrieval3(2), 127–163 (2000) https://doi.org/10.1023/A:1009953814988
Reference 53
- Resolution
- metadata mismatch
- doi, observed 2026-06-28T23:12:46.255340Z
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 d0ac747c-5991-4460-8788-f3d23158545e · outbound
This paper cites Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:47.030512Z
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 0d91cea8-1404-4e2c-8b93-a55ea1a815f9 · outbound
This paper cites Spectral Analysis on Graph-like Spaces / by Olaf Post.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Spectral Analysis on Graph-like Spaces / by Olaf Post
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a08c5ff-dae2-4968-8a7f-2a45ea9b1d49 · outbound
This paper cites C., Singh, A., Frey, N.
Graph Neural Networks Are Not Continuous Across Graph Resolutions C., Singh, A., Frey, N
Reference 56
- Resolution
- verified exact
- doi, observed 2026-06-28T23:12:46.255181Z
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 e1a8362f-0783-431b-8229-3740df3f21be · outbound
This paper cites M., Gama, F., Baraniuk, R.
Graph Neural Networks Are Not Continuous Across Graph Resolutions M., Gama, F., Baraniuk, R
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:46.261155Z
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 797dc866-4b11-4fcf-a2a3-43c774629073 · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-06-28T23:08:13.285717Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d0be8c57-db1f-470a-9eef-9ca55585a629 · outbound
This paper cites an unresolved cited work.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Unresolved cited work
Reference 59
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Observation afa7d1ac-e551-4b26-bd2d-dc6c42626ecd · outbound
This paper cites The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009.doi:10.1109/TNN.2008.2005605.
Graph Neural Networks Are Not Continuous Across Graph Resolutions The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009.doi:10.1109/TNN.2008.2005605
Reference 60
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- arxiv_id, observed 2026-06-28T23:12:46.247244Z
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Observation f4492fcc-39a8-4982-aa19-f2d8be36b86b · outbound
This paper cites Collective classification in network data.AI Magazine, 29(3):93, Sep.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Collective classification in network data.AI Magazine, 29(3):93, Sep
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Observation 0b051835-2adb-4cde-87f5-0f66ad8103a3 · outbound
This paper cites An Introduction to Measure Theory.
Graph Neural Networks Are Not Continuous Across Graph Resolutions An Introduction to Measure Theory
Reference 62
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Observation ce714ad5-606c-4d11-85a5-853f06bb8f42 · outbound
This paper cites Mathematical Methods in Quantum Mechanics.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Mathematical Methods in Quantum Mechanics
Reference 63
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Observation a84377a4-25d8-4d95-a8c9-ef09fa8ecfa8 · outbound
This paper cites Graph attention networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Graph attention networks
Reference 64
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Observation 4d977f79-410b-416b-b928-d672544968f1 · outbound
This paper cites Stability of neural networks on riemannian manifolds.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Stability of neural networks on riemannian manifolds
Reference 65
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Observation 251e1bdd-72b6-4335-a30c-37b5d498fc72 · outbound
This paper cites Stability to deformations of manifold filters and manifold neural networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Stability to deformations of manifold filters and manifold neural networks
Reference 66
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Observation 0a9457f7-d17b-4d41-abc0-1c4a3dc98fb8 · outbound
This paper cites Geometric graph filters and neural networks: Limit properties and discriminability trade-offs.IEEE Transactions on Signal Processing, 72:2244–2259.
Graph Neural Networks Are Not Continuous Across Graph Resolutions Geometric graph filters and neural networks: Limit properties and discriminability trade-offs.IEEE Transactions on Signal Processing, 72:2244–2259
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Observation 15e113e3-e7f4-4c8d-bfe3-f42e2b74ea0a · outbound
This paper cites On the hölder continuity of matrix functions for normal matrices.
Graph Neural Networks Are Not Continuous Across Graph Resolutions On the hölder continuity of matrix functions for normal matrices
Reference 68
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Observation 72913037-e2d1-4632-8ebd-fc3fe9607f69 · outbound
This paper cites doi: 10.1103/physrevlett.120.145301.
Graph Neural Networks Are Not Continuous Across Graph Resolutions doi: 10.1103/physrevlett.120.145301
Reference 69
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Observation 71f4e796-7251-4f43-9478-d909988f10d1 · outbound
This paper cites How powerful are graph neural networks? In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019.
Graph Neural Networks Are Not Continuous Across Graph Resolutions How powerful are graph neural networks? In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Reference 70
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Observation a44b6853-bb36-485a-906d-4975524331cb · outbound
This paper cites How framelets enhance graph neural networks.
Graph Neural Networks Are Not Continuous Across Graph Resolutions How framelets enhance graph neural networks
Reference 71
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Observation a4dd0e1e-853f-4862-b9fa-3955028b104c · outbound
This paper cites and Lerman, G.
Graph Neural Networks Are Not Continuous Across Graph Resolutions and Lerman, G
Reference 72
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Pith citing papers
Observation 5bd77990-75d0-41ab-ae74-e55ffedf6776 · inbound
Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization cites this paper.
Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization Graph Neural Networks Are Not Continuous Across Graph Resolutions
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