Paper Citation Record · LEDGER

Generative Models as Distributions of Functions

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2102.04776.

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

pith.paper-citation-record.v1
2102.04776 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 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:23:10.501398Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T17:12:24.411261Z

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 566d1921-0867-49ab-85c3-1cc0cec04da0 · inbound

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases cites this paper.

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases Generative Models as Distributions of Functions

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-12T20:23:10.501398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5441adf-da83-483e-bede-5496587cd6ac · inbound

Geometric Neural Process Fields cites this paper.

Geometric Neural Process Fields Generative Models as Distributions of Functions

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-09T12:34:02.112931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3d0005f-c5ea-4c6c-a088-7f688168e56e · inbound

Temporal Variational Implicit Neural Representations cites this paper.

Temporal Variational Implicit Neural Representations Generative Models as Distributions of Functions

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T11:45:38.381515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d777ef92-5e26-4025-a6bc-9eb3180fb94b · inbound

Revisiting Neural Processes via Fourier Transform and Volterra Series cites this paper.

Revisiting Neural Processes via Fourier Transform and Volterra Series Generative Models as Distributions of Functions

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:12:24.412766Z

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.