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Paper Citation Record · LEDGER

Optimization for Neural Operators can Benefit from Width

As of 10 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2502.00705.

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

pith.paper-citation-record.v1
2502.00705 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:09:06.193665Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

17 of 17 outbound references displayed

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  • verified fuzzy4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cf8d7397-3e59-4f96-8673-1b1157e74512 · outbound

This paper cites inner product.

Optimization for Neural Operators can Benefit from Width inner product

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-09T18:09:06.414382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a80ba389-3a34-46a2-bf3f-d1abadfef01d · outbound

This paper cites This is the same setup as in (Wang et al., 2021a; Lu et al., 2021).

Optimization for Neural Operators can Benefit from Width This is the same setup as in (Wang et al., 2021a; Lu et al., 2021)

Reference 5

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raw_fallback, observed 2026-08-09T18:09:06.379812Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4b5e47a8-8753-45dc-a2ee-271065636733 · outbound

This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

Optimization for Neural Operators can Benefit from Width FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 9

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Observation 44881555-2367-4afb-8cee-bbbcbd33f699 · outbound

This paper cites Derivative-enhanced Deep Operator Network.

Optimization for Neural Operators can Benefit from Width Derivative-enhanced Deep Operator Network

Reference 10

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Observation b4bd3570-ee9e-4fb1-bb91-df6b507bbcb1 · outbound

This paper cites Factorized Fourier Neural Operators.

Optimization for Neural Operators can Benefit from Width Factorized Fourier Neural Operators

Reference 11

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Observation 43ffd216-a57e-43e6-bbcb-fb6babdf3fa8 · outbound

This paper cites Long-time integration of parametric evolution equations with physics-informed DeepONets.

Optimization for Neural Operators can Benefit from Width Long-time integration of parametric evolution equations with physics-informed DeepONets

Reference 13

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verified exact
local_arxiv, observed 2026-08-09T18:09:06.242761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 977e1cc1-4a56-4c70-a8b8-ae9117334e3a · outbound

This paper cites Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.

Optimization for Neural Operators can Benefit from Width Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling

Reference 14

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Observation f5b4aef9-179b-47d5-9971-b5268fe140dd · outbound

This paper cites an unresolved cited work.

Optimization for Neural Operators can Benefit from Width Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2b4d4fee-f02f-48dc-810b-bc7a93f861b0 · outbound

This paper cites data” refers to the ground truth (obtained by a standard numerical solver) and “pred.

Optimization for Neural Operators can Benefit from Width data” refers to the ground truth (obtained by a standard numerical solver) and “pred

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-09T18:09:06.403381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ddac2dd9-7958-4461-ba2f-75cd64452184 · outbound

This paper cites an unresolved cited work.

Optimization for Neural Operators can Benefit from Width Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T18:09:06.186994Z digest=sha256:71e276d2b31ab75242c46feab21f8f83f1b3eaf159f8ee2bb735e5bdc8c404fc

Observation 68e8658c-c2f0-4691-945b-d87789d10fae · outbound

This paper cites All solutions are calculated for a single viscosity ν = 0.01.

Optimization for Neural Operators can Benefit from Width All solutions are calculated for a single viscosity ν = 0.01

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-09T18:09:06.368016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ab8dfd71-69ca-4b52-a4fa-338ac5688f49 · outbound

This paper cites Learning the Hodgkin-Huxley Model with Operator Learning Techniques.

Optimization for Neural Operators can Benefit from Width Learning the Hodgkin-Huxley Model with Operator Learning Techniques

Reference 2004

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verified exact
local_arxiv, observed 2026-08-09T18:09:06.344369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e202523b-e0a0-465c-ad87-1d1c79bd6c7b · outbound

This paper cites On the influence of over-parameterization in manifold based surrogates and deep neural operators.

Optimization for Neural Operators can Benefit from Width On the influence of over-parameterization in manifold based surrogates and deep neural operators

Reference 2017

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verified exact
local_arxiv, observed 2026-08-09T18:09:06.318006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ba64d7af-7cfe-4830-ab66-ac6a819e6496 · outbound

This paper cites A Convergence Theory for Deep Learning via Over-Parameterization.

Optimization for Neural Operators can Benefit from Width A Convergence Theory for Deep Learning via Over-Parameterization

Reference 2019

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Observation 322c640b-22ae-49e4-ade6-f4b698436ef6 · outbound

This paper cites A physics-informed variational DeepONet for predicting the crack path in brittle materials.

Optimization for Neural Operators can Benefit from Width A physics-informed variational DeepONet for predicting the crack path in brittle materials

Reference 2022

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source=pdf_text observed=2026-08-09T18:09:06.132230Z digest=sha256:a7fae1819872057690c83dbcec4179525f6a2552cabaae0305bd38083e7c95a0

Observation ee82c852-7e9e-4895-b913-2e07d3c58f90 · outbound

This paper cites A learning-based multiscale method and its application to inelastic impact problems.

Optimization for Neural Operators can Benefit from Width A learning-based multiscale method and its application to inelastic impact problems

Reference 2023

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verified exact
local_arxiv, observed 2026-08-09T18:09:06.289833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7fef951f-b81b-4719-b970-92c9341e855f · outbound

This paper cites Multipole Graph Neural Operator for Parametric Partial Differential Equations.

Optimization for Neural Operators can Benefit from Width Multipole Graph Neural Operator for Parametric Partial Differential Equations

Reference 2024

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