Pith. sign in

Paper Citation Record · LEDGER

Aggregating distribution forecasts from deep ensembles

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2204.02291.

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

pith.paper-citation-record.v1
2204.02291 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:16:04.720445Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T17:52:52.140609Z

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 a35e671b-c29f-4ba5-8656-df3512e19ca9 · inbound

Probabilistic intraday electricity price forecasting using generative machine learning cites this paper.

Probabilistic intraday electricity price forecasting using generative machine learning Aggregating distribution forecasts from deep ensembles

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T13:16:04.720445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:16:04.720445Z digest=sha256:57a7b1c19781bc01c6dff0791a79ec3bc55a7b9b1f7ccf65849bc65f9680770e

Observation c2df90cf-44eb-4ef0-828c-a6fba71ddef3 · inbound

Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods cites this paper.

Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods Aggregating distribution forecasts from deep ensembles

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-05T17:52:52.283739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-05T17:52:49.225989Z digest=sha256:2cd6588312c8c4908b92b52ccd2b6a7b9d8685e41c9d5943f29843e7bebf556a