Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T04:50:08.142215Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2607.13609.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T04:50:08.142215Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
44 of 44 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 96cec369-b856-44c6-b1a5-755dea79cc13 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs 1977 , publisher =
Reference 1
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Observation 14828fca-869c-4f69-b521-4d969f6f8ef2 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs 1998 , publisher =
Reference 2
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Observation 6a967a88-6b00-455d-a905-fe21e344dce3 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Physica D: Nonlinear Phenomena , volume =
Reference 3
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Observation 11f6b936-dbbd-4e8f-8f83-468900c0a642 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs 1984 , publisher =
Reference 4
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Observation 85af5dfd-7ff8-466f-b6af-98676141a053 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs IEEE Transactions on Pattern Analysis and Machine Intelligence , volume =
Reference 5
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Observation 198a2046-ae29-4dd8-8fde-af71e4cef38b · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Statistical ranking and combinatorial
Reference 6
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Observation 307b182b-f765-4b7d-af63-8a65871f15a5 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 7
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Observation 67be788c-dc8c-480d-a542-14694e38a4a8 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs and Benson, Austin R
Reference 8
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Observation 546948da-b16d-4072-95d9-042b91f6e57c · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs IEEE Signal Processing Magazine , volume =
Reference 9
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Observation f7f04078-5413-43dd-816b-5fb03dfd5384 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 10
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Observation 9e037213-bfba-4032-b74b-8488a4009b85 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Semi-supervised learning using
Reference 11
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Observation 889e98cd-ace5-4f28-902c-775ada5ca9cc · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Advances in Neural Information Processing Systems (NeurIPS) , volume =
Reference 12
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Observation ac5dd884-b77e-45a8-94a3-577b2d82fac8 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Journal of Machine Learning Research , volume =
Reference 13
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Observation b6259dbe-c37c-4215-8b34-eeae8c096477 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 14
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Observation 7cdff7aa-a3e0-4a6d-b318-2d67a2d3bd71 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 15
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Observation 2a4032d3-4259-48df-81b3-867d367907c2 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 16
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Observation 6cff73a2-eafb-48c5-8f11-e3247eb967ae · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) , pages =
Reference 17
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Observation bd20f549-ef7f-49b4-bc33-d68207e44841 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs IEEE Global Conference on Signal and Information Processing (GlobalSIP) , pages =
Reference 18
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Observation 32a016fa-e133-498a-95bf-05d095472045 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Learning on Graphs Conference (LoG) , series =
Reference 19
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Observation fbcdc22e-157a-47c9-9cf4-8446d7171029 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs IEEE Signal Processing Magazine , volume =
Reference 20
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Observation e3c7dde9-6cc4-482d-a197-e9e209c7399d · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Unresolved cited work
Reference 21
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Observation 3f5e0a8a-e3b9-406a-aa67-4fce2378f642 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Advances in Neural Information Processing Systems (NeurIPS) , year =
Reference 22
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Observation 8854c4e7-c93e-4164-bf27-144bb54a9b76 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs L aplacian eigenmaps for dimensionality reduction and data representation
Reference 23
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Observation 3661412e-096a-409c-bb0c-1788a9a670cb · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Chamberlain, Pietro Li \`o , and Michael M
Reference 24
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Observation 10b7158d-f35c-4145-90ea-564f15c82f17 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Doyle and J
Reference 25
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Observation 18ff7289-489d-4fb5-b693-f18da4ab281b · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Random walks for image segmentation
Reference 26
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Observation ac772d6d-dc2e-47dd-a770-8cf8fa46b227 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Rank-Deficient and Discrete Ill-Posed Problems: Numerical Aspects of Linear Inversion
Reference 27
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Observation 86cae011-ae64-487f-8746-d25ab2b1dd73 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs MSGNN : A spectral graph neural network based on a novel magnetic signed L aplacian
Reference 28
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Observation f6dd1829-a5a8-4516-87f2-d30e3924d2d3 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Schaub, Santiago Segarra, and Austin R
Reference 29
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Observation e9c5ea2e-b4e7-42a8-9554-4c1dbbcf7cc5 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Statistical ranking and combinatorial H odge theory
Reference 30
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Observation 40e9838a-77fa-4f25-ad55-f14e10f163a4 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs H odge L aplacians on graphs
Reference 31
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Observation 7753103f-0c94-457e-adcb-39401de1582f · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Marques, Santiago Segarra, and Gonzalo Mateos
Reference 32
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Observation ccebdd24-45e6-4c6d-8928-f56717c8d4ec · outbound
Reference 33
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Observation 8724b7f8-a0eb-46e6-8991-919b50a11d05 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Rudin, Stanley Osher, and Emad Fatemi
Reference 34
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Observation 0d678430-5396-4e6d-a67b-fc2a58a7be35 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Schaub and Santiago Segarra
Reference 35
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Observation 1ec09ee9-e4d9-4aa0-ab18-8b66b43efa12 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Schaub, Austin R
Reference 36
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Observation f7bb133b-d0ca-4d27-9665-5575920d3cec · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Shuman, Sunil K
Reference 37
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Observation edf03872-2dc5-4f97-ad7d-186329624a8a · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Tikhonov and Vasiliy Y
Reference 38
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Observation 5264f9d8-3a5e-44fc-9143-b220f11a77e6 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Smola, and Ryan J
Reference 39
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Observation 8a1abd0f-4f7a-4972-8c92-a1be9564e8a3 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs M ag N et: A neural network for directed graphs
Reference 40
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Observation 0fd69fcd-4da6-40f2-a760-3fd58fd79936 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs PairNorm : Tackling oversmoothing in GNN s
Reference 41
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Observation 3d32a799-9f50-4b0f-aa07-baefa194187d · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Lal, Jason Weston, and Bernhard Sch \"o lkopf
Reference 42
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Observation 8c37011d-969e-469f-ae8f-4593455c4aa0 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Dirichlet energy constrained learning for deep graph neural networks
Reference 43
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Observation 2e93b9e9-4666-4224-b948-f685b83b6e34 · outbound
Gauge-Invariant, Parameter-Insensitive Regularization for Potential Recovery from Flow on Directed Graphs Semi-supervised learning using G aussian fields and harmonic functions
Reference 44
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No inbound Pith citation observations are available.