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Paper Citation Record · LEDGER

Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2204.01618.

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

pith.paper-citation-record.v1
2204.01618 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:52:23.316107Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T05:17:18.148195Z

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 4444837a-56b8-413f-bf60-437d7688c493 · inbound

Uncertainty separation via ensemble quantile regression cites this paper.

Uncertainty separation via ensemble quantile regression Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T12:52:23.316107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:52:23.316107Z digest=sha256:5ed8a6f3a6ab852667b62c8247dde78e218ba9922c2a6ca7165d2cedb6ba5027

Observation 573f65eb-8e11-40a8-9c5b-8f936fdc198a · inbound

Random-Set Graph Neural Networks cites this paper.

Random-Set Graph Neural Networks Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:17:18.149980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T05:15:55.175024Z digest=sha256:7ed6586d9f08009f85502cd795675d56159ff83f8adc790894516d4c409a11bf