Paper Citation Record · LEDGER

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events

As of 22 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 2 inbound Pith citation observations for arXiv:2412.14048.

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

pith.paper-citation-record.v1
2412.14048 v1

Coverage vector

measured 51 of 51 reference resolution

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One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:37:35.343282Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T00:15:52.374911Z

Reference resolution

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation ff1e4e41-b1f5-4320-a7f7-92a7af15d819 · outbound

This paper cites Rajendra Acharya, Vladimir Makarenkov, and Saeid Nahavandi.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Rajendra Acharya, Vladimir Makarenkov, and Saeid Nahavandi

Reference 1

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Observation 3503022e-f420-490a-9d67-836df46688bf · outbound

This paper cites Abdullah, Masoud M.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Abdullah, Masoud M

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.553558Z

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Observation 77f72159-aa27-456c-9a1f-b5f457f65658 · outbound

This paper cites Abdullah, Masoud M.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Abdullah, Masoud M

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.540418Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c042de8a-4128-4d02-901d-72611f36dd75 · outbound

This paper cites Uncertainty quantification for hydrological models based on neural networks: the dropout ensemble.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Uncertainty quantification for hydrological models based on neural networks: the dropout ensemble

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.524350Z

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Observation b3050969-51c8-406a-9cd4-3804329a4aa2 · outbound

This paper cites Deep evidential regression.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Deep evidential regression

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.511711Z

Source-reported events for the cited work

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Observation abdb1b70-944a-491e-ab68-e3d32c471f53 · outbound

This paper cites Adaptive precipitation nowcasting using deep learning and ensemble modeling.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Adaptive precipitation nowcasting using deep learning and ensemble modeling

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.499668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8e67698f-6217-4d1d-b34f-6885d34e1e80 · outbound

This paper cites Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting, 2024.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.487513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5fda648c-2c56-42d5-8c73-e66f414b7f0f · outbound

This paper cites Seasonal Arctic sea ice forecasting with probabilistic deep learning.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Seasonal Arctic sea ice forecasting with probabilistic deep learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.475795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 545ee482-ef77-4478-b6d3-7d5543ffbbc2 · outbound

This paper cites Rainformer: Features extraction balanced network for radar-based precipitation nowcasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Rainformer: Features extraction balanced network for radar-based precipitation nowcasting

Reference 9

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Observation a47818db-c2e9-4218-b4df-39e43f9330ed · outbound

This paper cites Uncertainty quantification for data-driven weather models, 2024.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Uncertainty quantification for data-driven weather models, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.454160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93a8f7ca-6106-4e17-be86-2303a56b4afd · outbound

This paper cites Blei and Jon D.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Blei and Jon D

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.441641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2283cf69-8aad-4e59-814c-3414845173ac · outbound

This paper cites IFS Documentation CY47R3 - Part V Ensemble prediction system.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events IFS Documentation CY47R3 - Part V Ensemble prediction system

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.427425Z

Source-reported events for the cited work

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Observation 464c00f3-59d8-4ddc-a621-c0a3572186f5 · outbound

This paper cites Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:34:09.008626Z

Source-reported events for the cited work

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Observation 4396ebc6-a605-4613-8a18-d35de21f2f99 · outbound

This paper cites Broad-unet: Multi-scale feature learning for nowcasting tasks.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Broad-unet: Multi-scale feature learning for nowcasting tasks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.415157Z

Source-reported events for the cited work

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Observation cb4c788b-6058-45aa-80fe-6a4c224d0c9e · outbound

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

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Dropout as a bayesian approximation: representing model uncertainty in deep learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.403008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 819493b8-f043-441f-88c8-07a2ac889621 · outbound

This paper cites Prediff: Precipitation nowcasting with latent diffusion models.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Prediff: Precipitation nowcasting with latent diffusion models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.390135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2fc22903-ab77-4286-9ac8-6975f7ad9ec8 · outbound

This paper cites Earthformer: Exploring space-time transformers for earth system forecasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Earthformer: Exploring space-time transformers for earth system forecasting

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.377874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 009d0e00-0230-48b3-96c2-8a4224da7e03 · outbound

This paper cites Probabilistic forecasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Probabilistic forecasting

Reference 18

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Observation 87035e97-8d67-402b-933b-7dd08734376f · outbound

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Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Unresolved cited work

Reference 19

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Observation c5767499-389c-4f68-9d8b-bc3f46cf9803 · outbound

This paper cites CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling

Reference 20

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Observation 99820e7a-5220-44bf-8506-4525ab2f3305 · outbound

This paper cites The GOES-R series: a new generation of geostationary environmental satellites.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events The GOES-R series: a new generation of geostationary environmental satellites

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.345974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e205b00c-8b50-4478-aaa3-eabde693199e · outbound

This paper cites Disentangling physical dynamics from unknown factors for unsupervised video prediction.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Disentangling physical dynamics from unknown factors for unsupervised video prediction

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.332491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 673ea3cf-4983-4b0b-8f69-1fe097222a0c · outbound

This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 23

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Observation 0cdc10af-817c-4bfd-83da-d0b001d6a32b · outbound

This paper cites Gustafsson, Martin Danelljan, and Thomas B.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Gustafsson, Martin Danelljan, and Thomas B

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.319853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1a270a4b-1876-48e4-9837-d3b1e47a6cd7 · outbound

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

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.308048Z

Source-reported events for the cited work

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Observation 36bc5e1f-e151-4ea7-b7f5-4657a4ba759f · outbound

This paper cites Learning skillful medium-range global weather forecasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Learning skillful medium-range global weather forecasting

Reference 26

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Observation f1741781-2850-4cf8-82ef-0ccd341a07fd · outbound

This paper cites Ensemble size: How suboptimal is less than infinity? Q.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Ensemble size: How suboptimal is less than infinity? Q

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T12:34:08.702750Z

Source-reported events for the cited work

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Observation 98327c65-d9ec-4b1b-8a38-a032a147fb41 · outbound

This paper cites 3d high-quality magnetic resonance image restoration in clinics using deep learning.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events 3d high-quality magnetic resonance image restoration in clinics using deep learning

Reference 28

Resolution: verified exact; raw_fallback, observed 2026-08-11T12:34:08.960861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad5d5959-a243-4a64-9ffc-06f31c1be5c0 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Swin transformer: Hierarchical vision transformer using shifted windows

Reference 29

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Source-reported events for the cited work

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Observation 1baeb43d-ca1d-47b0-b3ab-4efaa130a006 · outbound

This paper cites A bayesian deep learning approach to near-term climate prediction.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events A bayesian deep learning approach to near-term climate prediction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.281552Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 967a8718-71c9-497f-bb40-cca4df58f33d · outbound

This paper cites McDermott and Christopher K.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events McDermott and Christopher K

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.269925Z

Source-reported events for the cited work

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Observation d739290e-7b0e-4680-97c2-e37022423fd7 · outbound

This paper cites Ezhilarasan.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Ezhilarasan

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.258254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6c9951cc-97d4-4ef7-a143-655449c75897 · outbound

This paper cites Statistical field theory.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Statistical field theory

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.246638Z

Source-reported events for the cited work

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Observation 117cc5ab-6de2-4c73-9b98-a93895ac7c51 · outbound

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

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 34

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Observation b7035c13-3388-4e39-b13d-3b963bf04e13 · outbound

This paper cites Andersson, Andrew El-Kadi, Do- minic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter Battaglia, Remi Lam, and Matthew Willson.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Andersson, Andrew El-Kadi, Do- minic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter Battaglia, Remi Lam, and Matthew Willson

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.234350Z

Source-reported events for the cited work

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Observation 128b2c18-8159-4606-8168-7b5a4699d93e · outbound

This paper cites Raftery, Tilmann Gneiting, Fadoua Balabdaoui, and Michael Polakowski.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Raftery, Tilmann Gneiting, Fadoua Balabdaoui, and Michael Polakowski

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.218954Z

Source-reported events for the cited work

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Observation 7af0d3af-d438-49b7-9b19-eb897b7f1d23 · outbound

This paper cites Skilful pre- cipitation nowcasting using deep generative models of radar.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Skilful pre- cipitation nowcasting using deep generative models of radar

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.205844Z

Source-reported events for the cited work

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Observation 40a49fe1-2df8-4c02-9e29-2ac8033834cd · outbound

This paper cites Deep learning and process understanding for data-driven earth system science.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Deep learning and process understanding for data-driven earth system science

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.193753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 487dece0-0fa8-4729-a40b-747fdca748fb · outbound

This paper cites Schreck, David John Gagne II au2, Charlie Becker, William E.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Schreck, David John Gagne II au2, Charlie Becker, William E

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.179644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e89f46ab-5dde-4add-a5f8-64a2c49350c6 · outbound

This paper cites Evidential deep learning to quantify classification uncertainty.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Evidential deep learning to quantify classification uncertainty

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.168650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf9e54c8-e25a-45a6-b19f-299942813442 · outbound

This paper cites Convolutional LSTM network: A machine learning approach for precipitation nowcasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Convolutional LSTM network: A machine learning approach for precipitation nowcasting

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.157895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b1a2b5f8-4c59-431f-82f7-c06bd8d3b798 · outbound

This paper cites Mc Lean Sloughter, Adrian E.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Mc Lean Sloughter, Adrian E

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.146551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2aeabb28-7262-4917-8838-2badce3893a0 · outbound

This paper cites Reliable oral cancer classification framework with bayesian deep learning.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Reliable oral cancer classification framework with bayesian deep learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.135304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a729e361-2cc8-4f6b-bf35-5c906af45cc4 · outbound

This paper cites A bayesian approach for uncertainty quantification of extreme precipitation projections including climate model interdependency and nonstationary bias.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events A bayesian approach for uncertainty quantification of extreme precipitation projections including climate model interdependency and nonstationary bias

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.122981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 82440a6d-9b4f-4d47-905f-b974f222544c · outbound

This paper cites Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T12:34:08.774202Z

Source-reported events for the cited work

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Observation 4ad11db3-1cc4-4da9-8162-64cb7e1ad321 · outbound

This paper cites SEVIR: A storm event imagery dataset for deep learning applications in radar and satellite meteorology.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events SEVIR: A storm event imagery dataset for deep learning applications in radar and satellite meteorology

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.107362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0311458b-dd4a-4e29-b6c6-ee07475483ea · outbound

This paper cites Eidetic 3D LSTM: A model for video prediction and beyond.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Eidetic 3D LSTM: A model for video prediction and beyond

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.092395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e87c70a3-42c5-404b-bd61-8ed2387ede9d · outbound

This paper cites PredRNN: A recurrent neural network for spatiotemporal predictive learning.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events PredRNN: A recurrent neural network for spatiotemporal predictive learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.079296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0d8ddcd-b547-43aa-9833-4e469fe8406d · outbound

This paper cites Diffcast: A unified framework via residual diffusion for precipitation nowcasting.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Diffcast: A unified framework via residual diffusion for precipitation nowcasting

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.067038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ed309ddd-8aee-48a9-a51b-bf5ecbe9d073 · outbound

This paper cites Jordan, and Jianmin Wang.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Jordan, and Jianmin Wang

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.054245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8ab3fa67-800e-40d3-9243-59386c8590e7 · outbound

This paper cites The development of the NCEP global ensemble forecast system version 12.

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events The development of the NCEP global ensemble forecast system version 12

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:34:09.040635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation f96cccdc-6e19-4c86-8361-09fe7caf0879 · inbound

Breaking the Statistical Similarity Trap in Extreme Convection Detection cites this paper.

Breaking the Statistical Similarity Trap in Extreme Convection Detection Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:35.343282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dee49749-7bc2-4ba4-b7c6-6558dcd527a5 · inbound

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification cites this paper.

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:15:52.377772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.