Paper Citation Record · LEDGER

Fast PDE-constrained optimization via self-supervised operator learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.13297.

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

pith.paper-citation-record.v1
2110.13297 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:41:09.851287Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T20:32:45.663523Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 f11a5806-a012-4cae-a96b-3c51b30a0606 · inbound

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators cites this paper.

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators Fast PDE-constrained optimization via self-supervised operator learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:09.851287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d257d4a1-6c78-4047-aee4-4224f629b29b · inbound

Towards Real Time Control of Water Engineering with Nonlinear Hyperbolic Partial Differential Equations cites this paper.

Towards Real Time Control of Water Engineering with Nonlinear Hyperbolic Partial Differential Equations Fast PDE-constrained optimization via self-supervised operator learning

Reference 118

Resolution: unresolved; no resolver link, observed 2026-08-03T16:11:53.870189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a354286-a7e2-4e1b-abb1-225a344e6662 · inbound

A Single-Loop Bilevel Deep Learning Method for Optimal Control of Obstacle Problems cites this paper.

A Single-Loop Bilevel Deep Learning Method for Optimal Control of Obstacle Problems Fast PDE-constrained optimization via self-supervised operator learning

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T12:12:35.261209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d57287b-2b86-43b6-a801-5ec903e41e29 · inbound

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects cites this paper.

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects Fast PDE-constrained optimization via self-supervised operator learning

Reference 225

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:32:45.664792Z

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 7ed03c0d-6c12-4229-bd7a-d590d2971a55 · inbound

Real-time optimal control with shallow recurrent decoder networks cites this paper.

Real-time optimal control with shallow recurrent decoder networks Fast PDE-constrained optimization via self-supervised operator learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T12:53:07.307884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.