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Paper Citation Record · LEDGER

A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2010.12493.

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

pith.paper-citation-record.v1
2010.12493 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:51:03.235846Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:28:53.296806Z

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 ad0408f7-7bf1-480c-a865-bb90cef571f0 · inbound

Universal Time-Series Representation Learning: A Survey cites this paper.

Universal Time-Series Representation Learning: A Survey A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

Reference 187

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:28:53.300348Z

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=2026-05-24T04:26:45.527625Z digest=sha256:0e3780300d8ebf55cbeae79cacdc529f848ee2ab7bdeb4d17223ad4b31d19adb

Observation d0b8608f-bf92-4ab4-8ae0-29a633dc2a58 · inbound

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis cites this paper.

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:03.235846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:51:03.235846Z digest=sha256:a4bb2074630fb54fe9263fab1a558cafd90ffb5afee5d4ea7c33ab115c663b64

Observation d2aea54e-6650-4e60-87f2-08179c7ad566 · inbound

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification cites this paper.

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

Reference 182

Resolution
unresolved
no resolver link, observed 2026-08-06T23:26:54.393479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:26:54.393479Z digest=sha256:f6418b6bdb3439d3e87b94651b5019ed2820d26f0df47c4785fced3e66bf856c

Observation 6dbdc11a-37cd-4bdf-9398-bde38d2c1a0d · inbound

DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification cites this paper.

DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:21:00.727339Z

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=2026-05-10T15:33:14.027429Z digest=sha256:0236e5545bb8a10366448817e0f36c2d57ad23cbf47ceaec9ec9ab830550a6c3