Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2205.09438.
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 2026-08-07T14:51:21.571889Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 41775334-c6a2-4926-8f96-5bf98e390e67 · inbound
Computational Math with Neural Networks is Hard cites this paper.
Computational Math with Neural Networks is Hard Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:21.571889Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b715cde0-a913-43e9-bed4-0aebbdc9fdbc · inbound
Approximating Hartree-Fock theory via an efficiently local reformulation cites this paper.
Approximating Hartree-Fock theory via an efficiently local reformulation Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
Reference 101
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T12:02:06.355574Z
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 d9944370-3cbd-4109-8338-412ba88fa93c · inbound
Is Variational Monte Carlo Robust? Sharp Moment Thresholds and Heavy-tailed Stochastic Optimization cites this paper.
Is Variational Monte Carlo Robust? Sharp Moment Thresholds and Heavy-tailed Stochastic Optimization Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T04:30:32.824415Z
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 9e556001-21c9-4338-b351-6310a7537ee3 · inbound
Is Variational Monte Carlo Robust? Sharp Moment Thresholds and Heavy-tailed Stochastic Optimization cites this paper.
Is Variational Monte Carlo Robust? Sharp Moment Thresholds and Heavy-tailed Stochastic Optimization Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:19:06.807731Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.