Paper Citation Record · LEDGER

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2606.09923.

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

pith.paper-citation-record.v1
2606.09923 v1

Coverage vector

measured 35 of 35 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-27T18:46:59.707637Z

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 4b516ce5-e01e-420f-8f35-d108e2a27cb4 · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:37:25.904412Z

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Observation b0cc59c0-9b1b-428d-bb74-087a5f9b63e8 · outbound

This paper cites Uncertainty sets for image classifiers using conformal prediction.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Uncertainty sets for image classifiers using conformal prediction

Reference 2

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Observation dd27abc0-9b89-478f-aa4a-7fdddac9a4cd · outbound

This paper cites Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:37:25.922041Z

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Observation a5859ffb-c9df-443a-bd22-0f7a0968943e · outbound

This paper cites Machine learning for fluid mechanics.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Machine learning for fluid mechanics

Reference 4

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Observation ee8a11f0-174d-4d13-8e6d-a62044059c48 · outbound

This paper cites Conformal prediction: A unified review of theory and new challenges.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Conformal prediction: A unified review of theory and new challenges

Reference 5

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Observation 4336d0b5-174d-45be-99a1-321b57087042 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 4339448a-4f72-4eca-bc2a-2fa342601a1b · outbound

This paper cites Adaptive Conformal Inference Under Distribution Shift.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Adaptive Conformal Inference Under Distribution Shift

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.925744Z

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Observation f40789e7-9a85-42ad-8801-845cca998613 · outbound

This paper cites Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation d58f7e98-1ae5-492d-8924-917a0a09cfa5 · outbound

This paper cites Physics-informed machine learning.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Physics-informed machine learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation e4acd7f9-5f98-4556-8925-03a32e18e4a9 · outbound

This paper cites Building high accuracy emulators for scientific simulations with deep neural operators.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Building high accuracy emulators for scientific simulations with deep neural operators

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation aeea1359-5838-42e5-8e7a-274a558a4bf9 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? In Advances in Neural Information Processing Systems (NeurIPS), 2017.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation What uncertainties do we need in bayesian deep learning for computer vision? In Advances in Neural Information Processing Systems (NeurIPS), 2017

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 18f1d3e0-7b53-446f-9d0b-41cf8fa6f0f5 · outbound

This paper cites Neural operator: Learning maps between function spaces with applications to pdes.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Neural operator: Learning maps between function spaces with applications to pdes

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation a8ddb448-5452-4ded-8e62-a060f49ccf59 · outbound

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

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation f284141e-bd4a-4f0d-b012-f06c1ff9b0cc · outbound

This paper cites Distribution-free predictive inference for regression.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Distribution-free predictive inference for regression

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 602f2bb5-bbc7-43ea-a65c-3395bb7b2249 · outbound

This paper cites Neural operator: Graph kernel network for partial differential equations.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Neural operator: Graph kernel network for partial differential equations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 8e5e4fac-ce1e-4d21-966f-bc389f4f7ce9 · outbound

This paper cites Fourier neural operator for parametric partial differential equations.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Fourier neural operator for parametric partial differential equations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation a3b5f8d3-2d7a-4009-b3ac-d35c0e9e1b6a · outbound

This paper cites Transmission in strained graphene subjected to laser and magnetic fields.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Transmission in strained graphene subjected to laser and magnetic fields

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.928623Z

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Observation 6f6b0cc2-6db8-401f-9946-6c56e49aedb2 · outbound

This paper cites Latent Outlier Exposure for Anomaly Detection with Contaminated Data.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Latent Outlier Exposure for Anomaly Detection with Contaminated Data

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.907185Z

Source-reported events for the cited work

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Observation c95d89c8-5c96-4895-972a-9ffcf73b01f4 · outbound

This paper cites Dynamic Partial Computation Offloading for the Metaverse in In-Network Computing.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Dynamic Partial Computation Offloading for the Metaverse in In-Network Computing

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.922623Z

Source-reported events for the cited work

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Observation 91101285-bac5-475b-832a-2e6325b7d21c · outbound

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

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Deeponet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 8e8a2083-97a6-4348-bc08-97bca9fa98a6 · outbound

This paper cites Long-term evolution of multimass rotating star clusters.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Long-term evolution of multimass rotating star clusters

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.931268Z

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Observation 20273fd9-1a4f-4060-9d03-8d904499dcf2 · outbound

This paper cites Topologically protected vortex transport via chiral-symmetric disclination.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Topologically protected vortex transport via chiral-symmetric disclination

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.901238Z

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Observation f410a36d-f82d-4f63-9e25-4e0386012d56 · outbound

This paper cites Nvidia modulus: A framework for building, training, and fine-tuning deep learning models using physics-based data.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Nvidia modulus: A framework for building, training, and fine-tuning deep learning models using physics-based data

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation aab50d2a-652a-4e94-9650-c8fbb0a2461e · outbound

This paper cites Inductive confidence machines for regression.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Inductive confidence machines for regression

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation f5e19801-4eb3-48e8-858b-74762753b475 · outbound

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

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:37:25.919181Z

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Observation 99d7c6fe-0a52-43fc-8372-a3b6073191c8 · outbound

This paper cites Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 7b2a01db-8bd7-4164-97cc-b793032a3cfc · outbound

This paper cites Uncertainty Quantification and Deep Ensembles.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Uncertainty Quantification and Deep Ensembles

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.919732Z

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Observation a3f94879-96b0-42db-aa29-49a163f7f7c1 · outbound

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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Conformalized quantile regression

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 82e9449e-c694-4ea0-b5f0-abd59fd719b7 · outbound

This paper cites With malice toward none: Assessing uncertainty via equalized coverage.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation With malice toward none: Assessing uncertainty via equalized coverage

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 9a9aaf76-d3d3-4a1b-b40a-7d5d778fd42d · outbound

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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation A comparison of some conformal quantile regression methods

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation A tutorial on conformal prediction

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation f4514e7f-d701-45ef-b2a3-75f1473a5b7a · outbound

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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Learned simulators for turbulence

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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This paper cites PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.924649Z

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Observation da1322bc-9fd4-4f4e-9a29-54650b77c2a6 · outbound

This paper cites Algorithmic Learning in a Random World.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Algorithmic Learning in a Random World

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Observation 50afcd27-d552-4362-9668-17e3ea69a4b5 · outbound

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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation Conformal prediction interval for dynamic time-series

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-27T18:46:59.707637Z

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Pith citing papers

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