Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
One-shot learning for solution operators of partial differential equations
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2104.05512.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:21:43.134940Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T16:49:58.384030Z
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 daed2437-53ba-49d7-b10c-d08dab62f7ef · inbound
Neural-operator element method: Efficient and scalable finite element method enabled by reusable neural operators cites this paper.
Neural-operator element method: Efficient and scalable finite element method enabled by reusable neural operators One-shot learning for solution operators of partial differential equations
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:21:43.134940Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1602db4f-6914-46a1-8f3f-e0248e8b9ef3 · inbound
Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements cites this paper.
Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements One-shot learning for solution operators of partial differential equations
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:22:49.299650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 231e116d-19d2-494c-b4f6-5806a804b859 · inbound
PD-SOVNet: A Physics-Driven Second-Order Vibration Operator Network for Estimating Wheel Polygonal Roughness from Axle-Box Vibrations cites this paper.
PD-SOVNet: A Physics-Driven Second-Order Vibration Operator Network for Estimating Wheel Polygonal Roughness from Axle-Box Vibrations One-shot learning for solution operators of partial differential equations
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:15:51.738566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 517bbd3f-5b31-42b6-b3e2-f8a8b6028501 · inbound
Towards a Foundation Model for the Martian Atmosphere cites this paper.
Towards a Foundation Model for the Martian Atmosphere One-shot learning for solution operators of partial differential equations
Reference 170
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T19:05:00.825269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 263e2383-8312-4fc8-b4c5-6c6d64b1041e · inbound
A Zeroth-Order Deep Learning Method for Fully Nonlinear Parabolic Partial Differential Equations with Unknown Coefficients cites this paper.
A Zeroth-Order Deep Learning Method for Fully Nonlinear Parabolic Partial Differential Equations with Unknown Coefficients One-shot learning for solution operators of partial differential equations
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T16:49:58.385656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.