Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Wasserstein Learning of Deep Generative Point Process Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1705.08051.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:51:24.693787Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T13:51:24.754093Z
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 b8688506-928b-47e7-a571-032cfdef13a5 · inbound
Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing cites this paper.
Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing Wasserstein Learning of Deep Generative Point Process Models
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T13:51:24.757856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2000322e-86ad-4330-8992-3c199b78c08a · inbound
In-Context Learning of Temporal Point Processes with Foundation Inference Models cites this paper.
In-Context Learning of Temporal Point Processes with Foundation Inference Models Wasserstein Learning of Deep Generative Point Process Models
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:54:19.864848Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.