Pith. sign in

Paper Citation Record · LEDGER

Fast PDE-constrained optimization via self-supervised operator learning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:07:33.255714Z

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
  • 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 56ed9853-56e6-47e2-903b-c7990b1d6092 · inbound

Optimal Control Operator Perspective and a Neural Adaptive Spectral Method cites this paper.

Optimal Control Operator Perspective and a Neural Adaptive Spectral Method Fast PDE-constrained optimization via self-supervised operator learning

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-11T14:07:33.255714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:07:33.255714Z digest=sha256:4ac19316cbbcdcb2a9094ed078700605961896cc10d4ecad2c7f237a94cb48ac

Observation fe88ee91-a964-4e27-a6b4-db9cf1416bbe · inbound

Deep Operator Networks for Bayesian Parameter Estimation in PDEs cites this paper.

Deep Operator Networks for Bayesian Parameter Estimation in PDEs Fast PDE-constrained optimization via self-supervised operator learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T19:06:10.096512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:06:10.096512Z digest=sha256:0e9d4bcda0a78ed84b215e3ca33681a5644006b4b60f416bb9b56f94e27a3077

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.

source=pdf_text observed=2026-08-07T00:41:09.851287Z digest=sha256:1972d0e99ca4ccdcfdcff727013ebc7d3d3abb6ae9a45cce483f9840dfb5321e

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.

source=pdf_text observed=2026-08-03T16:11:53.870189Z digest=sha256:dd8ed32edaf6ab1bd9d5d85192dae269d8efd08f9a5c03b92ae5924a0e7ed8bb

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.

source=arxiv_source observed=2026-08-03T12:12:35.261209Z digest=sha256:91c353631664bfdacd10441f87daf600b4152d959da9c9d5be6f5b9dbbb3ddf8

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-19T20:28:37.206593Z digest=sha256:6626369465044b33547a9699e9960e5c89866af719991659dbab8791be2a29fe

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.

source=pdf_text observed=2026-08-01T12:53:07.307884Z digest=sha256:8de3cee26b0c6f3b6413db3216db83a6f3c034629f8a4916f20db706f0b2fd41