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Paper Citation Record · LEDGER

A Graph Autoencoder Approach to Causal Structure Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1911.07420.

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

pith.paper-citation-record.v1
1911.07420 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:47:18.675026Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

54
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5f686c8a-3c6f-4520-be3d-236f7f7ce4f9 · inbound

Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond cites this paper.

Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond A Graph Autoencoder Approach to Causal Structure Learning

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T16:47:18.675026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:47:18.675026Z digest=sha256:94a4faee6c3bc27ab3629cb3e23b321d611053d73de3fdd69455a739e5bfe334

Observation 3b5f1491-2fa2-47d8-83ed-dd3492f28733 · inbound

ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning cites this paper.

ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning A Graph Autoencoder Approach to Causal Structure Learning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T10:18:07.459599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:18:07.459599Z digest=sha256:5ade90b1e866c4bcd1d86b98fa7acc3b3afdc0b77da265e19af0e2a2f541a6e1

Observation 9be73a5b-c92a-4392-a14b-cea46642065b · inbound

Toward Temporal Causal Representation Learning with Tensor Decomposition cites this paper.

Toward Temporal Causal Representation Learning with Tensor Decomposition A Graph Autoencoder Approach to Causal Structure Learning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T16:15:39.569493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:15:39.569493Z digest=sha256:ae460c0c6c2b103247278e7f663cf5b70f2add292bd6fa3a386323304176a779

Observation 2d497066-86cf-4f1d-bf11-f1ba5e88f67b · inbound

TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violations cites this paper.

TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violations A Graph Autoencoder Approach to Causal Structure Learning

Reference 232

Resolution
verified exact
arxiv_id, observed 2026-05-08T19:09:02.689817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T19:04:40.817413Z digest=sha256:e8ad8765530a1254f3a33df1fa3aad1d7821580e2f33f1d86e0e14376cb89838

Observation 74ebf365-1e4a-4ee3-a2c0-7ad569ed61cb · inbound

SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery cites this paper.

SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery A Graph Autoencoder Approach to Causal Structure Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T13:39:08.210176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:39:08.210176Z digest=sha256:36c85f7b418b762f3fb317bef099aa8cae9fcd20fd3afaedd4b0429c162b5879