Paper Citation Record · LEDGER

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2507.11574.

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

pith.paper-citation-record.v1
2507.11574 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:44.618938Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:18:26.556600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:46:02.378512Z

Reference resolution

38 of 38 outbound references displayed

verified exact2
verified fuzzy24
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b4addca-317e-418b-b13b-bac561d34a4c · outbound

This paper cites an unresolved cited work.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:25:50.033195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e1d9a6ea-c28c-47c1-8d94-4607417ce2b1 · outbound

This paper cites From Proxies to Fields: Spatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators From Proxies to Fields: Spatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.066252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17499541-1319-49ca-afc7-9903722920b0 · outbound

This paper cites Virtual sensing to enable real-time monitoring of inaccessible locations & unmeasurable parameters.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Virtual sensing to enable real-time monitoring of inaccessible locations & unmeasurable parameters

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.137757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 830f564a-9a21-4dac-b310-e267f08d1d60 · outbound

This paper cites Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.864413Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0781e987-a335-48f9-ab70-032440cd590d · outbound

This paper cites Deep neural operator-driven real-time inference to enable digital twin solutions for nuclear energy systems.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Deep neural operator-driven real-time inference to enable digital twin solutions for nuclear energy systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.645389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0ceec502-5548-4b42-803b-89f06d0ca227 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Fourier Neural Operator for Parametric Partial Differential Equations

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.348296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a40fd036-cce9-4260-9076-d0b2b93c3168 · outbound

This paper cites Spherical fourier neural operators: Learning stable dynamics on the sphere.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Spherical fourier neural operators: Learning stable dynamics on the sphere

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.526137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 96c14388-33a4-4bc5-83b0-61cf24f0c2ac · outbound

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

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 8

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Source-reported events for the cited work

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Observation 9405c482-5bf8-4659-b0d8-877615380592 · outbound

This paper cites Multipole graph neural operator for parametric partial differential equations.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Multipole graph neural operator for parametric partial differential equations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.636924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 186df835-fd43-4f26-bdee-7b94d60032ec · outbound

This paper cites Wavelet neural operator for solving parametric partial differential equations in computational mechanics problems.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Wavelet neural operator for solving parametric partial differential equations in computational mechanics problems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.723427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2d3d4e9-d706-4544-9f49-ffdb68267473 · outbound

This paper cites A wavelet neural operator based elastography for localization and quantification of tumors.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators A wavelet neural operator based elastography for localization and quantification of tumors

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.397246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0bb523c-6421-44cf-b6ca-b05ca8aecf53 · outbound

This paper cites Learning nonlinear operators via deeponet based on the universal approximation theorem of operators.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Learning nonlinear operators via deeponet based on the universal approximation theorem of operators

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.880168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a606847-1a75-4f43-bee7-11330c1bddf5 · outbound

This paper cites an unresolved cited work.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:42.980779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e7745e0-1d6a-4f4f-b703-c801c3934944 · outbound

This paper cites Mionet: Learning multiple-input operators via tensor product.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Mionet: Learning multiple-input operators via tensor product

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:43.093566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0926038-72ff-4cf1-9014-235fa9270bc4 · outbound

This paper cites Sequential deep operator networks (s-deeponet) for predicting full-field solutions under time-dependent loads.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Sequential deep operator networks (s-deeponet) for predicting full-field solutions under time-dependent loads

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.250368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2e1335b5-acb1-48db-a461-ed843a3feaaa · outbound

This paper cites Predictions of transient vector solution fields with sequential deep operator network.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Predictions of transient vector solution fields with sequential deep operator network

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:49.057046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 92db63d2-9a95-4d6c-8c56-27ec458afee0 · outbound

This paper cites Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:25:45.068075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation edeca6ab-f9eb-4b53-b708-15e80a549b06 · outbound

This paper cites Fully convolutional network enhanced deeponet-based surrogate of predicting the travel-time fields.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Fully convolutional network enhanced deeponet-based surrogate of predicting the travel-time fields

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.920440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2966884f-d824-4a89-a39d-be8bec188ffd · outbound

This paper cites Porous-deeponet: Learning the solution operators of parametric reactive transport equations in porous media.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Porous-deeponet: Learning the solution operators of parametric reactive transport equations in porous media

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:43.553381Z

Source-reported events for the cited work

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Observation 1959583a-9656-43fc-bf84-b14ec4803494 · outbound

This paper cites Ai-driven uncertainty quantification & multi-physics approach to evaluate cladding materials in a microreactor.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Ai-driven uncertainty quantification & multi-physics approach to evaluate cladding materials in a microreactor

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.732802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6900e211-1504-482f-b412-bf5d918387e6 · outbound

This paper cites Degradation-Aware and Machine Learning-Driven Uncertainty Quantification in Crystal Plasticity Finite Element: Texture-Driven Plasticity in 316L Stainless Steel.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Degradation-Aware and Machine Learning-Driven Uncertainty Quantification in Crystal Plasticity Finite Element: Texture-Driven Plasticity in 316L Stainless Steel

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:25:44.784920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 42f0184a-7eb3-4ca4-b809-80fca7e14b02 · outbound

This paper cites Ai-driven non-intrusive uncertainty quantification of advanced nuclear fuels for digital twin-enabling technology.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Ai-driven non-intrusive uncertainty quantification of advanced nuclear fuels for digital twin-enabling technology

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.583356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c804663-3fd4-4c63-9b73-83277f329ffe · outbound

This paper cites Practical applications of gaussian process with uncertainty quantification and sensitivity analysis for digital twin for accident-tolerant fuel.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Practical applications of gaussian process with uncertainty quantification and sensitivity analysis for digital twin for accident-tolerant fuel

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.422461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 53d7a999-2998-4037-a37a-ee64b2945a10 · outbound

This paper cites Uncertainty quantification and sensitivity analysis for digital twin enabling technology: Application for bison fuel performance code.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Uncertainty quantification and sensitivity analysis for digital twin enabling technology: Application for bison fuel performance code

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.260987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c80bcb73-c93b-4ceb-8e3e-43d28670ba7b · outbound

This paper cites Quantitative risk assessment of a high power density small modular reactor (SMR) core using uncertainty and sensitivity analyses.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Quantitative risk assessment of a high power density small modular reactor (SMR) core using uncertainty and sensitivity analyses

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:48.094141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7453ff49-510a-4b63-b15c-a0f13033f24c · outbound

This paper cites Multi-criteria decision making under uncertainties in composite materials selection and design.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Multi-criteria decision making under uncertainties in composite materials selection and design

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:47.854631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eff413c4-2542-415a-ab8b-c51e330262b4 · outbound

This paper cites Bayesian neural networks: An introduction and survey.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Bayesian neural networks: An introduction and survey

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:47.515343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d058b0d-a991-46e2-b3f5-64e0c44595fb · outbound

This paper cites Hands- on bayesian neural networks—a tutorial for deep learning users.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Hands- on bayesian neural networks—a tutorial for deep learning users

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:47.208745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05aaea96-9994-45ee-9717-cc4372916530 · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 29

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Source-reported events for the cited work

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Observation cfcbd673-c7a3-4fd0-8fdc-fd6f99cc7cba · outbound

This paper cites Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:46.959605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ef992ed3-7abd-4aab-9e7d-6f6ee3d01682 · outbound

This paper cites Distribution free uncertainty quantification for neuroscience-inspired deep neural operators.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Distribution free uncertainty quantification for neuroscience-inspired deep neural operators

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:46.768218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 678c41f0-0b79-46bf-80cc-6be4a93cdfd7 · outbound

This paper cites Gaussian processes in machine learning.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Gaussian processes in machine learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:46.634618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b3b4e5ed-eeb0-4478-937b-88371195e7e2 · outbound

This paper cites Randomized prior functions for deep reinforcement learning.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Randomized prior functions for deep reinforcement learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:46.384082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bd1b060a-6bac-4ec7-8650-78f97d30407a · outbound

This paper cites Analytical model for estimating terrestrial cosmic ray fluxes nearly anytime and anywhere in the world: Extension of parma/expacs.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Analytical model for estimating terrestrial cosmic ray fluxes nearly anytime and anywhere in the world: Extension of parma/expacs

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:46.121147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ad05f7ce-ce7c-4257-ac16-0582b316c11f · outbound

This paper cites Analytical model for estimating the zenith angle dependence of terrestrial cosmic ray fluxes.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Analytical model for estimating the zenith angle dependence of terrestrial cosmic ray fluxes

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:45.890876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2aa07288-0717-46ff-b607-5485cabcf59b · outbound

This paper cites EXPACS: EXcel-based program for calculating atmospheric cosmic-ray spectrum.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators EXPACS: EXcel-based program for calculating atmospheric cosmic-ray spectrum

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:45.709565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 410ebdea-b202-4a23-ace2-917e4c04f3db · outbound

This paper cites Benchmark study of particle and heavy-ion transport code system using shielding integral benchmark archive and database for accelerator-shielding experiments.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Benchmark study of particle and heavy-ion transport code system using shielding integral benchmark archive and database for accelerator-shielding experiments

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:45.532719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f8f797a-e8ed-4767-ba03-723fdfd87aec · outbound

This paper cites Recent improvements of the particle and heavy ion transport code system–phits version 3.33.

Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators Recent improvements of the particle and heavy ion transport code system–phits version 3.33

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:45.407462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 5a0a84e3-77b4-408b-b0e6-906e4c7c196f · inbound

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators cites this paper.

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:02.381557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9cda41db-e3c8-458e-9ecc-d451ec14ebe4 · inbound

Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields cites this paper.

Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T00:18:26.556600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.