Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Variational Learning is Effective for Large Deep Networks
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.17641.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:39:18.391365Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T20:40:08.506330Z
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 7d189caa-36d8-40a1-b892-3bf352f1fcca · inbound
Optimization Guarantees for Square-Root Natural-Gradient Variational Inference cites this paper.
Optimization Guarantees for Square-Root Natural-Gradient Variational Inference Variational Learning is Effective for Large Deep Networks
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:39:18.391365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e298c473-0caa-4aa3-9d62-4bc69c10f1c1 · inbound
Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing cites this paper.
Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing Variational Learning is Effective for Large Deep Networks
Reference 27
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-18T10:02:31.767495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation de62a576-759e-4e53-928a-17820d8b22d2 · inbound
Gaussian Mean Field Variational Inference can Overestimate Predictive Variance cites this paper.
Gaussian Mean Field Variational Inference can Overestimate Predictive Variance Variational Learning is Effective for Large Deep Networks
Reference 30
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T20:40:08.507744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.