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Paper Citation Record · LEDGER

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.03225.

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

pith.paper-citation-record.v1
1910.03225 v4

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 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:06:23.467407Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T01:49:22.169167Z

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 fe00fe9a-bfd1-4754-9196-1de5d2090950 · inbound

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions cites this paper.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T21:06:23.467407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:06:23.467407Z digest=sha256:8f5d59e7b9f7a09edc6bad4a4a7c6320a4a5fed8c876d9ce749de3e3eea7bc90

Observation 118683d3-ff6b-4923-97bb-6f4b2d1ecdfe · inbound

SemiConLens: Visual Analytics for 2D Semiconductor Discovery cites this paper.

SemiConLens: Visual Analytics for 2D Semiconductor Discovery NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:45:57.434778Z

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=2026-05-10T16:32:22.840426Z digest=sha256:2790274b4a836baa8a8695e10e8e81f3da45ef37e00a65935066988fcb27743d

Observation fab827d5-6e9d-47da-910d-622de9339726 · inbound

Reimagining SED Fitting with Cosmological Galaxy Simulations and Machine Learning cites this paper.

Reimagining SED Fitting with Cosmological Galaxy Simulations and Machine Learning NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T01:49:22.170680Z

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=2026-06-26T20:12:36.338298Z digest=sha256:117a12646f1d782be215d2b538a753c48ae267c823e4ac1ad72a11b7652a23ff

Observation b0d8fa8c-011d-4195-9809-7dd7e667f62f · inbound

Frugal Bayesian Optimization: Scalable Surrogates for Data- and Resource-Limited Discovery cites this paper.

Frugal Bayesian Optimization: Scalable Surrogates for Data- and Resource-Limited Discovery NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-03T11:21:50.735778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:21:50.735778Z digest=sha256:60e2cd39078927ff2fd15e197407356f0a837b7a2ee58f9da5944b3caf0696af