Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Local Lipschitz Bounds of Deep Neural Networks
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2004.13135.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T18:36:29.289465Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T12:38:16.916189Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
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 d2f0f9fc-82a7-491f-9d6a-e4ecbc3a6902 · inbound
A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANs cites this paper.
A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANs Local Lipschitz Bounds of Deep Neural Networks
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T18:36:29.289465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e33a1517-130b-4a82-ad16-d676d336066a · inbound
Pointwise Generalization in Deep Neural Networks cites this paper.
Pointwise Generalization in Deep Neural Networks Local Lipschitz Bounds of Deep Neural Networks
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:38:16.917608Z
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.
Observation e37e640f-c7e2-42c3-9dc5-53429cace672 · inbound
Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates cites this paper.
Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates Local Lipschitz Bounds of Deep Neural Networks
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T07:18:07.013582Z
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.
Observation fe6c29f9-df56-43f1-8d9f-43ba7e26caf5 · inbound
Operator Neural Jump ODEs: $L^2$-optimal prediction in function spaces cites this paper.
Operator Neural Jump ODEs: $L^2$-optimal prediction in function spaces Local Lipschitz Bounds of Deep Neural Networks
Reference 91
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T03:42:48.046690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.