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Paper Citation Record · LEDGER

Deep Ensembles Secretly Perform Empirical Bayes

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2501.17917.

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

pith.paper-citation-record.v1
2501.17917 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:17:06.472635Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T11:59:50.323783Z

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 cc21cd62-6150-4528-aed1-30ecd4035aa4 · inbound

Last Layer Empirical Bayes cites this paper.

Last Layer Empirical Bayes Deep Ensembles Secretly Perform Empirical Bayes

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T15:17:06.472635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:17:06.472635Z digest=sha256:8d4041ed73df8440f61d06a5f17d6e54dd26739ce8261110289ade3ddbcf963a

Observation 690e4616-4427-4b2a-9e49-8e152ba09b7f · inbound

Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials cites this paper.

Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials Deep Ensembles Secretly Perform Empirical Bayes

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T15:40:32.553972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:40:32.553972Z digest=sha256:9d3fc482a777fb61c80c5e667ac267298a794452fc52161dfd2e87f04037f437

Observation 1a89973e-ce3f-49dd-8668-bcc7d40680c4 · inbound

The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone cites this paper.

The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone Deep Ensembles Secretly Perform Empirical Bayes

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T07:36:37.783437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:36:37.783437Z digest=sha256:e07adf973de9d1ae538d0c9339b4bdeed68d42806f125fd6e572219ffd589b46

Observation 77be351d-4b09-4bb9-913e-d106f10600b9 · inbound

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation cites this paper.

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation Deep Ensembles Secretly Perform Empirical Bayes

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:22:09.048912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T22:20:32.857882Z digest=sha256:14fc8373975720a2d2de74ae06dea3d19b572ab54458478eecdd1fe1450e86e6

Observation 88cdd92c-80f1-465b-9a60-694575320fdb · inbound

Field-level weak lensing cosmology with $<100$ simulations using multifidelity simulation-based inference cites this paper.

Field-level weak lensing cosmology with $<100$ simulations using multifidelity simulation-based inference Deep Ensembles Secretly Perform Empirical Bayes

Reference 177

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T11:59:50.325797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T07:27:31.537264Z digest=sha256:7ec6d53cd1222731838f455affdff3da09f20823e06c4b2f6a9e3dffd057b5af

Observation 9a6a6fa1-d715-45d4-b819-c3bbecc98ea7 · inbound

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation cites this paper.

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation Deep Ensembles Secretly Perform Empirical Bayes

Reference 161

Resolution
unresolved
no resolver link, observed 2026-08-06T00:10:39.975567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:10:39.975567Z digest=sha256:847b07f5260e519941d1384d6dd13aab866735a97a972eb142fc1a6037009101