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Paper Citation Record · LEDGER

Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1707.03993.

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

pith.paper-citation-record.v1
1707.03993 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:53:19.171514Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:20:15.732616Z

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 bff74c06-4bf2-4de2-9c6c-5e79dd2f9d9b · inbound

Learning stochastic differential equations using RNN with log signature features cites this paper.

Learning stochastic differential equations using RNN with log signature features Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-14T11:53:19.171514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:53:19.171514Z digest=sha256:bb4869225fb7c55f8aa34f5a5306d1e7d8d8b8ae66a71c4ed35b62bc5bce8d51

Observation ec2dd22f-486c-4ce3-a0b7-2e61a3d39dcd · inbound

Deep Learning for Estimating Synaptic Health of Primary Neuronal Cell Culture cites this paper.

Deep Learning for Estimating Synaptic Health of Primary Neuronal Cell Culture Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:20:15.737888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T10:20:15.527502Z digest=sha256:6a4c3b7955bc8279063a5d48ac3d8bde7dfe98bbcba31af86d18da1e89ed6dc3