Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scalable Monte Carlo for Bayesian Learning
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.12751.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:59:07.079268Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T06:51:31.260898Z
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 e5536122-74de-4de5-b825-dde82da5ee32 · inbound
Diffusion piecewise exponential models for survival extrapolation using Piecewise Deterministic Monte Carlo cites this paper.
Diffusion piecewise exponential models for survival extrapolation using Piecewise Deterministic Monte Carlo Scalable Monte Carlo for Bayesian Learning
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:59:07.079268Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62f3eba5-aa95-4d31-98f6-0a71270a931c · inbound
Deep Learning Surrogates for Real-Time Gas Emission Inversion cites this paper.
Deep Learning Surrogates for Real-Time Gas Emission Inversion Scalable Monte Carlo for Bayesian Learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:55:48.152771Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cb6f55b-bfd9-45e1-8f5a-601e2519868c · inbound
gemlib.mcmc: composable kernels for Metropolis-within-Gibbs sampling schemes cites this paper.
gemlib.mcmc: composable kernels for Metropolis-within-Gibbs sampling schemes Scalable Monte Carlo for Bayesian Learning
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:51:31.268925Z
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.