Paper Citation Record · LEDGER

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels

As of 4 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.02886.

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pith.paper-citation-record.v1
2606.02886 v2

Coverage vector

measured 38 of 38 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-28T15:17:47.046216Z

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Reference resolution

38 of 38 outbound references displayed

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Outbound references

Observation 13dd07cf-7906-4df8-b756-5403dd3670e4 · outbound

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

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 1

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This paper cites doi: 10.1038/s41586-023-06185-3.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels doi: 10.1038/s41586-023-06185-3

Reference 2

Resolution: verified exact; doi, observed 2026-06-28T15:22:19.616619Z

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correction dated 2023-09-14. Source: crossref record 10.1038/s41586-023-06545-z->10.1038/s41586-023-06185-3:correction, observed 2026-07-11T03:00:24.47659+00:00. This notice travels one citation hop only.

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This paper cites an unresolved cited work.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 3

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This paper cites an unresolved cited work.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 4

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This paper cites Nature, 641 (8065), 1180--1187, doi:10.1038/s41586-025-09005-y, ://www.nature.com/articles/s41586-025-09005-y.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Nature, 641 (8065), 1180--1187, doi:10.1038/s41586-025-09005-y, ://www.nature.com/articles/s41586-025-09005-y

Reference 5

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 6

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 7

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This paper cites 1993 , publisher=.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels 1993 , publisher=

Reference 8

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 9

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Observation 5d6e22c5-273a-4595-8b71-4d9e0e45efc7 · outbound

This paper cites A systematic review of intermediate fusion in multimodal deep learning for biomedical applications , volume=.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels A systematic review of intermediate fusion in multimodal deep learning for biomedical applications , volume=

Reference 10

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 11

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This paper cites Strictly.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Strictly

Reference 12

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 13

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 14

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This paper cites an unresolved cited work.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 15

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This paper cites Hersbach, B.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Hersbach, B

Reference 16

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 17

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This paper cites Fast and robust fixed-point algorithms for independent component analysis.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Fast and robust fixed-point algorithms for independent component analysis

Reference 18

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 19

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 20

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 21

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 22

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This paper cites doi: 10.1126/science.adi2336.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels doi: 10.1126/science.adi2336

Reference 23

Resolution: verified exact; doi, observed 2026-06-28T15:22:19.608408Z

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Observation f7165328-a3ae-4096-bdb2-748df11ba3e5 · outbound

This paper cites AIFS -- ECMWF's data-driven forecasting system.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels AIFS -- ECMWF's data-driven forecasting system

Reference 24

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This paper cites an unresolved cited work.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 25

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Observation 00461c27-f1a3-41d9-8fc8-4160f4f5d058 · outbound

This paper cites Generative emulation of weather forecast ensembles with diffusion models.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Generative emulation of weather forecast ensembles with diffusion models

Reference 26

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 27

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This paper cites Biometrika , author =.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Biometrika , author =

Reference 28

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 29

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 30

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Observation 0b25623a-6067-4c1f-a995-332b27865af3 · outbound

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

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 31

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 32

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This paper cites WeatherBench 2: A Benchmark for the Next Generation of Data-Driven Global Weather Models.Journal of Advances in Modeling Earth Systems, 16(6).

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels WeatherBench 2: A Benchmark for the Next Generation of Data-Driven Global Weather Models.Journal of Advances in Modeling Earth Systems, 16(6)

Reference 33

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 34

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This paper cites Methods for comparing uncertainty quantifications for material property predictions.Machine Learning: Science and Technology, 1(2):025006, May 2020.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Methods for comparing uncertainty quantifications for material property predictions.Machine Learning: Science and Technology, 1(2):025006, May 2020

Reference 35

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels de la and Montgomery-Smith, S

Reference 36

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This paper cites When 𝜎2 𝑛 = 0: 𝑤 𝑗 = 1for all 𝜆 𝑗 > 0, so 𝐶𝑟 = Í𝑟 𝑗=1 𝑐2 𝑗 =∥ ˜𝜙(𝑥 ∗) ∥2 − ∥ ˜𝜙⊥ ∥2, giving 𝜎2 (𝑥∗)=∥ ˜𝜙⊥ ∥2.

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels When 𝜎2 𝑛 = 0: 𝑤 𝑗 = 1for all 𝜆 𝑗 > 0, so 𝐶𝑟 = Í𝑟 𝑗=1 𝑐2 𝑗 =∥ ˜𝜙(𝑥 ∗) ∥2 − ∥ ˜𝜙⊥ ∥2, giving 𝜎2 (𝑥∗)=∥ ˜𝜙⊥ ∥2

Reference 37

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Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels Unresolved cited work

Reference 38

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