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Paper Citation Record · LEDGER

Computing Lyapunov functions using deep neural networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2005.08965.

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

pith.paper-citation-record.v1
2005.08965 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:58:07.297385Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:41:29.743523Z

Reference resolution

0 of 0 outbound references displayed

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  • 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 222b423c-fc13-4075-9525-870d75c316dc · inbound

Sequentially learning regions of attraction from data cites this paper.

Sequentially learning regions of attraction from data Computing Lyapunov functions using deep neural networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:07.297385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:07.297385Z digest=sha256:cb98c73db2626f638a6ecb99a7afe568c8eddaf2b87b2c0f4dbad8fb4d6018d9

Observation 9b2a93b7-6fb6-4d08-b89c-a620341e1786 · inbound

HyParLyVe: Hyperplane Partitioning for Neural Lyapunov Verification cites this paper.

HyParLyVe: Hyperplane Partitioning for Neural Lyapunov Verification Computing Lyapunov functions using deep neural networks

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:41:29.746977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-07T04:21:40.258505Z digest=sha256:15d49adda797d636f8a92ac9a529518e08bceb55009b2e228347364d54281ae3