Paper Citation Record · LEDGER

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries

As of 8 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2502.10033.

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

pith.paper-citation-record.v1
2502.10033 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:43:57.911833Z

measured 33 of 33 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

33 of 33 outbound references displayed

verified exact0
verified fuzzy17
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5d0d7ae-e596-431e-9d8f-2e708b6b6573 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.584464Z

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 37597f43-2c4a-4ea7-a4e8-139a5063fc9f · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.726306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 734b6d5a-c43a-4280-8abe-baa48bee8716 · outbound

This paper cites Bhattacharya, B.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Bhattacharya, B

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.569650Z

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 b56070be-0fb5-410c-9e00-145e7cd35753 · outbound

This paper cites Bonet and R.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Bonet and R

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.560407Z

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 a75c944c-919b-4f15-9bf1-ef228d1b9ed9 · outbound

This paper cites Cotin, M.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Cotin, M

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.551434Z

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 8db08027-bcd9-434e-93bf-2cf6f9057fc4 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.542663Z

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 6cbbb0b8-0c62-4b4c-b888-f56016220181 · outbound

This paper cites Duprez, V.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Duprez, V

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.533592Z

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 4c649c9b-4b0a-4e7c-8374-897ab306df3f · outbound

This paper cites Duprez, V.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Duprez, V

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.523470Z

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 8101a0ba-e26e-4fe4-b354-5aac98910035 · outbound

This paper cites Duprez, V.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Duprez, V

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.514450Z

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 1c665bb5-6291-454e-953b-a373cdb1e424 · outbound

This paper cites Duprez and A.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Duprez and A

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.505382Z

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 b98d2489-b719-4f4f-b184-18bc6de0b327 · outbound

This paper cites Ern and J.-L.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Ern and J.-L

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.496744Z

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 76bfecf1-057b-461d-b950-c52e32ff8a25 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.487264Z

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 fbade7e1-9a1c-471e-b85b-002fe95a8453 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.762068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 041067d5-bc70-42c7-933b-d4a3ff010223 · outbound

This paper cites Nonlinearsolidmechanics: acontinuumapproachforengineeringscience, 2002.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Nonlinearsolidmechanics: acontinuumapproachforengineeringscience, 2002

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.432879Z

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 dfbca8f4-6bc6-4071-9c2e-12703dbca6e0 · outbound

This paper cites Neural Operator: Learning Maps Between Function Spaces.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Neural Operator: Learning Maps Between Function Spaces

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.768053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd45b811-c705-42d1-8b15-a4438264ab1d · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.330087Z

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 048ef137-40a0-4c59-a42b-f7c71e2d26cd · outbound

This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.774456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ccb2fca-40f8-43e7-8a01-1d6c7542bcff · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.231249Z

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 87d4f4f1-1da4-4aac-a3eb-e99eb4c78b05 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.207901Z

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 6c2292ae-bc54-4f36-a1c1-aa8070a5c058 · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.784050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b06b5eaf-58b2-4c6d-9d71-776e06b0dd3d · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.199200Z

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 d914ab5b-82a7-446d-a1aa-bfae24ab46e5 · outbound

This paper cites Meunier, G.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Meunier, G

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.189852Z

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 e7c675b5-019b-4c80-83ac-c9a7a1b683c9 · outbound

This paper cites Nastorg, M.-A.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Nastorg, M.-A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.180770Z

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 531ebc6a-c112-419d-b833-e8bd65acb813 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.171577Z

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 84a08b37-528e-4c26-8212-23cf0f7d9e4e · outbound

This paper cites Paszke, S.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Paszke, S

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.162538Z

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 327ccea8-2dea-4a6f-b33e-6ecf1c0c68a8 · outbound

This paper cites Raissi, P.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Raissi, P

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.152375Z

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 8224c654-5a87-4dad-ad22-0062f1ed6d99 · outbound

This paper cites Ronneberger, P.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Ronneberger, P

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.142665Z

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 3c3c99a8-36e6-450c-83ef-fb056a394a68 · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T19:43:57.808209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7bba733-2d83-462e-9791-2ce11f49ab7a · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.125913Z

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 a1aaacac-f0ea-40af-a86d-3bf55bfb3d58 · outbound

This paper cites Sirignano and K.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Sirignano and K

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.115406Z

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 9a27f943-7cdd-4263-bc57-3f6bf480252e · outbound

This paper cites an unresolved cited work.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:43:58.104897Z

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 367ec48b-812c-4afd-b69e-d39b7b33642d · outbound

This paper cites Yu et al.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Yu et al

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.092578Z

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 653da4e9-04ba-47d9-9ce6-7a7347dfd55c · outbound

This paper cites Zhu and N.

Phi-FEM-FNO: a new approach to train a Neural Operator as a fast PDE solver for variable geometries Zhu and N

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:43:58.025514Z

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.