Paper Citation Record · LEDGER

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2505.24505.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24505 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:26:17.845185Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy14
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62a0ab82-03f7-4451-bc36-998f9840b3ef · outbound

This paper cites An introduction to optimal power flow: Theory, formulation, and examples,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset An introduction to optimal power flow: Theory, formulation, and examples,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:20.600839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 480e2992-394f-45ab-a42b-3542ec9c88d3 · outbound

This paper cites Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:20.400069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2925a32-ac15-4068-a12e-c20ef51f51d1 · outbound

This paper cites Learning to optimize: A primer and a benchmark,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Learning to optimize: A primer and a benchmark,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:20.247152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation efb45673-025e-45f6-b0ef-ad67af5548d1 · outbound

This paper cites Deep unfolding for commu- nications systems: A survey and some new directions,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Deep unfolding for commu- nications systems: A survey and some new directions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:20.104444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6ea08e2a-d46d-423a-8e35-917e63fbeee2 · outbound

This paper cites Learning to solve decision problems over two timescales: An application to 5g puncturing,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Learning to solve decision problems over two timescales: An application to 5g puncturing,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.912647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71b2708c-bfda-4629-b9d9-2bdf0f3852b3 · outbound

This paper cites Amp-inspired deep net- works for sparse linear inverse problems,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Amp-inspired deep net- works for sparse linear inverse problems,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.767782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a2423f70-4b1d-4f8e-a9ff-d7194bb2da87 · outbound

This paper cites Optimal power flow using graph neural networks,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Optimal power flow using graph neural networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.592876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae078853-d3ff-4732-9022-de0a43a7e4b0 · outbound

This paper cites Deepopf: A feasibility- optimized deep neural network approach for ac optimal power flow problems,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Deepopf: A feasibility- optimized deep neural network approach for ac optimal power flow problems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.438497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a1a42c75-cb79-484c-9485-12237b0af9fb · outbound

This paper cites Unsupervised optimal power flow using graph neural networks,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Unsupervised optimal power flow using graph neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.219711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6fc929eb-ecb7-492a-9993-e1e2d85a9b68 · outbound

This paper cites Energ ´ıas renovables en uruguay.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Energ ´ıas renovables en uruguay

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:19.009162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0255e831-2405-44a9-a811-c6c99035af42 · outbound

This paper cites Graphs, convolutions, and neural networks: From graph filters to graph neural networks,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Graphs, convolutions, and neural networks: From graph filters to graph neural networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:18.782106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4bac01f4-1a75-49a9-824c-cd329b774a8e · outbound

This paper cites Stability properties of graph neural networks,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Stability properties of graph neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:18.603247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ad4cd271-09f2-412d-9950-657692cd6a6c · outbound

This paper cites pandapower — an open-source python tool for convenient modeling, analysis, and optimization of electric power systems,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset pandapower — an open-source python tool for convenient modeling, analysis, and optimization of electric power systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:18.343424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a9017a66-6eea-4b7a-a83b-79e707c5f19e · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework,.

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset Optuna: A next-generation hyperparameter optimization framework,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:18.143167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.