Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Predicting interacting Green's functions with neural networks
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2411.13644.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T14:10:13.326521Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T00:43:24.631902Z
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 b2aa3bb0-fa25-45d2-ba4e-f38f1c5f143e · inbound
Linear Foundation Model for Quantum Embedding: Data-Driven Compression of the Ghost Gutzwiller Variational Space cites this paper.
Linear Foundation Model for Quantum Embedding: Data-Driven Compression of the Ghost Gutzwiller Variational Space Predicting interacting Green's functions with neural networks
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T14:10:13.326521Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be5b9c56-e31b-47e1-9ad7-7f3596491264 · inbound
Neural networks as low-cost surrogates for impurity solvers in quantum embedding methods cites this paper.
Neural networks as low-cost surrogates for impurity solvers in quantum embedding methods Predicting interacting Green's functions with neural networks
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T00:43:24.635344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1233558f-9ae6-4943-8a4e-95caf50cd43f · inbound
Compact and Stable Representation of Real-Frequency Spectral Functions for Machine Learning cites this paper.
Compact and Stable Representation of Real-Frequency Spectral Functions for Machine Learning Predicting interacting Green's functions with neural networks
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T06:23:32.807246Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.