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Paper Citation Record · LEDGER

Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1703.00091.

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

pith.paper-citation-record.v1
1703.00091 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:37:51.368328Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T17:28:44.710193Z

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 6f60b18b-006b-4443-967a-68b5be75de3f · inbound

Training of Spiking Neural Networks with Expectation-Propagation cites this paper.

Training of Spiking Neural Networks with Expectation-Propagation Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T21:37:51.368328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:37:51.368328Z digest=sha256:ddc85302ba01fa6edd07c59de789011dc404d482b7cc0813b95ef390eb94d1d6

Observation fc0c5062-2d6b-4cd0-ae30-2e40337fec1f · inbound

Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning cites this paper.

Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-07-03T17:28:44.711387Z

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=2026-06-27T04:04:33.390770Z digest=sha256:b93fb71ebe248c2101652cfd194c4cb9c7c2a9fa24d730721cc23b5560e755c1