Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2303.13056.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T05:50:54.697860Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T03:27:34.825262Z
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 1fa3ab60-3608-4451-8def-b7590b32d9d3 · inbound
Fast Sampling of Cosmological Initial Conditions with Gaussian Neural Posterior Estimation cites this paper.
Fast Sampling of Cosmological Initial Conditions with Gaussian Neural Posterior Estimation Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
Reference 6
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-09T05:50:54.697860Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac7a71be-bdf9-4765-896e-4664a0fcf5a0 · inbound
DISCO-DJ II: a differentiable particle-mesh code for cosmology cites this paper.
DISCO-DJ II: a differentiable particle-mesh code for cosmology Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T11:25:28.451998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6603e0f-617e-4d61-bfcd-94d3f0b31e97 · inbound
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation cites this paper.
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:38:16.724246Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcf7e619-e1b4-42ed-b931-d5b026e462b3 · inbound
On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods cites this paper.
On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T00:31:19.404893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 26acd020-0709-4d71-9b2f-d8870070f33f · inbound
Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions cites this paper.
Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions Predicting the Initial Conditions of the Universe using a Deterministic Neural Network
Reference 60
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T03:27:34.826932Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.