Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.12849.
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 2026-08-05T13:25:26.774689Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T01:36:26.323176Z
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 c4bae55e-e2ff-4b5a-9926-72d63283c0b1 · inbound
Revisiting Deep AC-OPF cites this paper.
Revisiting Deep AC-OPF DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:25:26.774689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43f935f4-e791-433d-8fd8-3385fac757ee · inbound
Learning to Optimize by Differentiable Programming cites this paper.
Learning to Optimize by Differentiable Programming DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks
Reference 111
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:39:37.402279Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d111e39e-8ba0-4c9d-bac7-dd3bc196352f · inbound
Rethinking Neural Width for Alternating Current Optimal Power Flow Proxies cites this paper.
Rethinking Neural Width for Alternating Current Optimal Power Flow Proxies DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T01:36:26.325833Z
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.