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Paper Citation Record · LEDGER

Regularisation of Neural Networks by Enforcing Lipschitz Continuity

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1804.04368.

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

pith.paper-citation-record.v1
1804.04368 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:42:29.139112Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 0756ed86-08a6-4336-8912-4376b2db0b70 · inbound

Mean Spectral Normalization of Deep Neural Networks for Embedded Automation cites this paper.

Mean Spectral Normalization of Deep Neural Networks for Embedded Automation Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:35:08.557885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-25T00:31:54.457757Z digest=sha256:79de9659e82f3019970cc3fd3347e7376101b2a7371eb81672f9f5f6daf6d185

Observation 251c6fda-bfb6-4840-89d3-c6653e1707a2 · inbound

Robust Optimal Safe and Stability Guaranteeing Reinforcement Learning Control for Quadcopter cites this paper.

Robust Optimal Safe and Stability Guaranteeing Reinforcement Learning Control for Quadcopter Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:29.139112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:42:29.139112Z digest=sha256:8e4531ef85d46fc824ed925dcfde17b61ce7fbe0e02a8fb8e18623ca6a099f23

Observation a96ebaec-c6c9-46f4-97c4-0110ae53ad6a · inbound

Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics cites this paper.

Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:16.298420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:42:16.298420Z digest=sha256:2f53908d3e9e60f780f0fb1c8074331d2212cb095435ad2c6924e1eca8d5ce13

Observation 96a74b37-c08a-46bf-94e0-0f7377c0715c · inbound

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems cites this paper.

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Reference 106

Resolution
verified exact
arxiv_id, observed 2026-05-09T19:56:16.429432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-09T19:56:13.911743Z digest=sha256:324f57a101b7b87570b2867287f18dc0b11a91f16f78c77ac0648037a0a89725

Observation 83c96157-46ce-4dbd-aaa5-bc38a4055eba · inbound

Generating Bearing Vibration Signals at User-Specified Fault Probabilities Using PR-GAN and Counterfactual Methods cites this paper.

Generating Bearing Vibration Signals at User-Specified Fault Probabilities Using PR-GAN and Counterfactual Methods Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T13:22:01.236021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:22:01.236021Z digest=sha256:0868ce5188f79f0d201a22a996cbdf787991d7f5cb7ebfda2e420f345ea3b23f