Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Stochastic Gradient MCMC with Repulsive Forces
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1812.00071.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:15:47.968691Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T02:46:28.720088Z
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 eecf4bfc-bb03-4df9-976a-2d735f5edd0a · inbound
The Stein-log-Sobolev inequality and the exponential rate of convergence for the continuous Stein variational gradient descent method cites this paper.
The Stein-log-Sobolev inequality and the exponential rate of convergence for the continuous Stein variational gradient descent method Stochastic Gradient MCMC with Repulsive Forces
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:15:47.968691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7afbbd08-57d0-44bf-9ef2-6ef1e52a797b · inbound
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks cites this paper.
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Stochastic Gradient MCMC with Repulsive Forces
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T03:45:56.904658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 21616192-31e3-4614-948d-cc64127ac58e · inbound
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks cites this paper.
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Stochastic Gradient MCMC with Repulsive Forces
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T06:29:49.753668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 096eaf80-143c-4e9b-ba4c-15c7f57b25b5 · inbound
Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials cites this paper.
Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials Stochastic Gradient MCMC with Repulsive Forces
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T02:46:28.722663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 6f650c72-0cc2-47f5-ba57-16c5178a80e4 · inbound
Mean-Field Stochastic PDEs: Well-posedness and Quantitative Dimension-Free Propagation of Chaos cites this paper.
Mean-Field Stochastic PDEs: Well-posedness and Quantitative Dimension-Free Propagation of Chaos Stochastic Gradient MCMC with Repulsive Forces
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T18:51:11.094831Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.