AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble | Paper Citation Record

Observation 61fea041-917e-427b-982f-96648346748a · outbound

This paper cites Sustainable development agenda: 2030.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Sustainable development agenda: 2030

Reference 1

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Observation 3ccf8c56-929e-427d-abc3-7755aaded7e2 · outbound

This paper cites Six transformations to achieve the sustainable development goals.Nature sustainability, 2(9):805–814, 2019.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Six transformations to achieve the sustainable development goals.Nature sustainability, 2(9):805–814, 2019

Reference 2

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Observation 25772ec5-7550-42c3-921c-fdd257c3ecb2 · outbound

This paper cites A review of energy extraction from wind and ocean: Technologies, merits, efficiencies, and cost.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A review of energy extraction from wind and ocean: Technologies, merits, efficiencies, and cost

Reference 3

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This paper cites A large-scale review of wave and tidal energy research over the last 20 years.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A large-scale review of wave and tidal energy research over the last 20 years

Reference 4

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Observation bf54ae5e-e85a-4459-898e-e7d14a72a5ec · outbound

This paper cites Advanced wave energy conversion technologies for sustainable and smart sea: A comprehensive review.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Advanced wave energy conversion technologies for sustainable and smart sea: A comprehensive review

Reference 5

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Observation 38eb6e71-09ab-454f-b1ca-e755636679ba · outbound

This paper cites Wave energy utilization: A review of the technologies.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Wave energy utilization: A review of the technologies

Reference 6

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Observation 5d3b2e7d-0b03-46c5-9714-4479e94d30c6 · outbound

This paper cites Energy harvesting: solar, wind, and ocean energy conversion systems.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Energy harvesting: solar, wind, and ocean energy conversion systems

Reference 7

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Observation 7279efd0-76e0-40db-9998-2b21ee96ee16 · outbound

This paper cites Ocean wave energy converters: Status and challenges.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean wave energy converters: Status and challenges

Reference 8

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Observation a9d3f44a-1e0c-401f-96e7-2afc9d185b06 · outbound

This paper cites Ocean energy systems wave energy modelling task: Modelling, verification and validation of wave energy converters.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean energy systems wave energy modelling task: Modelling, verification and validation of wave energy converters

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.850923Z

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Observation 0c8ddaec-ef1a-43cd-a649-21e7aa8ce8db · outbound

This paper cites Wave energy conversion.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Wave energy conversion

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.810335Z

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Observation 611edb3d-ccba-42c1-9a91-49a9346891be · outbound

This paper cites Ocean wave energy conversion.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean wave energy conversion

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.765780Z

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Observation 4bade874-b1d0-4897-abf6-98352af24e75 · outbound

This paper cites Ocean wave energy conversion: resource, technologies and performance.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean wave energy conversion: resource, technologies and performance

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.664753Z

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Observation 1af9f9ce-d440-47f6-98db-8e6343974813 · outbound

This paper cites Short-term wave forecasting for real-time control of wave energy converters.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Short-term wave forecasting for real-time control of wave energy converters

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.610643Z

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Observation 2e14d0bf-5fa7-45f2-b4f7-a97a2885f6d1 · outbound

This paper cites A study of the prediction requirements in real-time control of wave energy converters.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A study of the prediction requirements in real-time control of wave energy converters

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.541087Z

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Observation f10e899d-3519-4ac6-bcde-fe540c8ec9de · outbound

This paper cites Wave energy converter control by wave prediction and dynamic programming.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Wave energy converter control by wave prediction and dynamic programming

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.508982Z

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Observation 33ce6b87-3007-478e-b0a2-5e1a8d397302 · outbound

This paper cites Optimizing ocean-wave energy extraction of a dual coaxial-cylinder wec using nonlinear model predictive control.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Optimizing ocean-wave energy extraction of a dual coaxial-cylinder wec using nonlinear model predictive control

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.472936Z

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Observation 67fde07f-e2af-4149-b8a2-68946a3624df · outbound

This paper cites In-ocean validation of a deterministic sea wave prediction (dswp) system leveraging x-band radar to enable optimal control in wave energy conversion systems.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble In-ocean validation of a deterministic sea wave prediction (dswp) system leveraging x-band radar to enable optimal control in wave energy conversion systems

Reference 17

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Observation 4cb5dfcd-374b-451a-8d8e-25653cdb9283 · outbound

This paper cites Experimental and computational analysis of elastomer membranes used in oscillating water column wecs.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Experimental and computational analysis of elastomer membranes used in oscillating water column wecs

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.390835Z

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Observation c668fa6d-6e57-4351-a9e9-53ac7ab5ce04 · outbound

This paper cites Wind waves: their generation and propagation on the ocean surface.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Wind waves: their generation and propagation on the ocean surface

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.366219Z

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Observation dc36178e-2c62-4028-90fc-7925e4c4b477 · outbound

This paper cites On the existence of a fully developed wind-sea spectrum.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble On the existence of a fully developed wind-sea spectrum

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.336837Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e4f2f7ce-3a82-4ad0-b257-ff86c5ed994e · outbound

This paper cites Water waves: The mathematical theory with applications, volume 36.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Water waves: The mathematical theory with applications, volume 36

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.314797Z

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Observation b891a607-0f60-475b-afc9-8ff4fd209f73 · outbound

This paper cites Dynamics and modelling of ocean waves.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Dynamics and modelling of ocean waves

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.273576Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 93942d63-70d0-4840-878d-82ccc3ce9866 · outbound

This paper cites Significant wave height prediction by using a spatial model.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Significant wave height prediction by using a spatial model

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.203931Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 405adcb2-8646-49ad-bdbb-008c34ee4653 · outbound

This paper cites Forecasting ocean waves: Comparing a physics-based model with statistical models.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Forecasting ocean waves: Comparing a physics-based model with statistical models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.134273Z

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Observation 8ff2ae9b-6b25-48e4-bc6a-a35ca5d2ad3a · outbound

This paper cites Ocean waves and oscillating systems: linear interactions including wave- energy extraction, volume 8.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean waves and oscillating systems: linear interactions including wave- energy extraction, volume 8

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.099593Z

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Observation 8d77e3db-ef2a-4c95-9efe-71e4e97b985f · outbound

This paper cites Evaluating the efficacy of svms, bns, anns and anfis in wave height prediction.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Evaluating the efficacy of svms, bns, anns and anfis in wave height prediction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.061556Z

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Observation 1ab4ecfb-5abb-4c8f-bd46-9ac8c6cff511 · outbound

This paper cites Nonlinear real time prediction of ocean surface waves.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Nonlinear real time prediction of ocean surface waves

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:11.009425Z

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Observation 082c08ac-7208-462a-a0ab-bcfe813a2acf · outbound

This paper cites A machine learning framework to forecast wave conditions.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A machine learning framework to forecast wave conditions

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.941194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 69c05ad7-4dfd-4c93-8d98-e8c471d46137 · outbound

This paper cites A novel model to predict significant wave height based on long short-term memory network.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A novel model to predict significant wave height based on long short-term memory network

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.883124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b5365337-62bc-4ab9-9cd0-1e3f6aa775c4 · outbound

This paper cites Improved short-term prediction of significant wave height by decomposing deterministic and stochastic components.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Improved short-term prediction of significant wave height by decomposing deterministic and stochastic components

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.855196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c199b909-50c6-443b-b026-f3af18de3ef8 · outbound

This paper cites Ocean wave energy forecasting using optimised deep learning neural networks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Ocean wave energy forecasting using optimised deep learning neural networks

Reference 31

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Source-reported events for the cited work

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Observation 2e7e51e4-2981-474d-95e5-47cfeef0710b · outbound

This paper cites Application of nested artificial neural network for the prediction of significant wave height.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Application of nested artificial neural network for the prediction of significant wave height

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.807624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c4e2959-45bf-4221-8237-78eb284d20c5 · outbound

This paper cites Spatial-temporal wave height forecast using deep learning and public reanalysis dataset.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Spatial-temporal wave height forecast using deep learning and public reanalysis dataset

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.742267Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 341786f7-950c-4cde-8fc8-d1e6a2475ce5 · outbound

This paper cites Instantaneous prediction of irregular ocean surface wave based on deep learning.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Instantaneous prediction of irregular ocean surface wave based on deep learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.669607Z

Source-reported events for the cited work

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Observation f396d4f8-b5d7-40d4-9cab-4d7876ef9b4a · outbound

This paper cites Prediction of near-field uni-directional and multi-directional random waves from far-field measurements with artificial neural networks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Prediction of near-field uni-directional and multi-directional random waves from far-field measurements with artificial neural networks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.545799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 92377580-15eb-47b1-9b45-f2fb9aa7689c · outbound

This paper cites Prediction of irregular wave (current)-induced pore water pressure around monopile using machine learning methods.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Prediction of irregular wave (current)-induced pore water pressure around monopile using machine learning methods

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.484516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8083c7d4-f982-49ed-b12c-8567c931fea6 · outbound

This paper cites A novel multivariable hybrid model to improve short and long-term significant wave height prediction.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A novel multivariable hybrid model to improve short and long-term significant wave height prediction

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.454749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0f6ea3d7-d615-4df2-a80a-d15dd048d144 · outbound

This paper cites Phase-resolved wave prediction with linear wave theory and physics-informed neural networks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Phase-resolved wave prediction with linear wave theory and physics-informed neural networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.304755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c1ef4bfb-f812-48c9-91a1-e9f163422125 · outbound

This paper cites Development of pyramid neural networks for prediction of significant wave height for renewable energy farms.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Development of pyramid neural networks for prediction of significant wave height for renewable energy farms

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.267361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ae7fbcb-cbbc-4dcf-974b-5041be0ddaa9 · outbound

This paper cites A wave forecasting method based on probabilistic diffusion lstm network for model predictive control of wave energy converters.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A wave forecasting method based on probabilistic diffusion lstm network for model predictive control of wave energy converters

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.199023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7121b68-bc1d-4eb2-a1ce-3a01bea9092a · outbound

This paper cites A numerical study on hydrodynamic performance of an inclined owc wave energy converter with nonlinear turbine–chamber interaction based on 3d potential flow.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A numerical study on hydrodynamic performance of an inclined owc wave energy converter with nonlinear turbine–chamber interaction based on 3d potential flow

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.136381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32ba8371-391f-412d-87d2-e24ebb70655e · outbound

This paper cites A numerical study on hydrodynamic energy conversions of owc-wec with the linear decomposition method under irregular waves.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A numerical study on hydrodynamic energy conversions of owc-wec with the linear decomposition method under irregular waves

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:10.017647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 51a1d0cb-14e8-449e-99f5-495e45afcac5 · outbound

This paper cites Uncertainty analysis of a wec model test experiment.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Uncertainty analysis of a wec model test experiment

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.971258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dc99cb41-f880-435e-94db-24c4ee2de862 · outbound

This paper cites Experimental study on hydrodynamic behavior and energy conversion of multiple oscillating-water-column chamber in regular waves.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Experimental study on hydrodynamic behavior and energy conversion of multiple oscillating-water-column chamber in regular waves

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.937316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41bb1711-574d-447a-994b-ad7a0801cf50 · outbound

This paper cites Experimental and numerical investigations on the solitary wave actions on a land-fixed owc wave energy converter.Energy, 282:128363, 2023.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Experimental and numerical investigations on the solitary wave actions on a land-fixed owc wave energy converter.Energy, 282:128363, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.904766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 398b4ac2-0aa0-4842-8beb-f1552636b85d · outbound

This paper cites Prediction of air pressure change inside the chamber of an oscillating water column–wave energy converter using machine-learning in big data platform.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Prediction of air pressure change inside the chamber of an oscillating water column–wave energy converter using machine-learning in big data platform

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.818405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 874e4c15-47d7-4400-a09c-b8def52f4a02 · outbound

This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.021325Z

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

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 48

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This paper cites What uncertainties do we need in bayesian deep learning for computer vision? Advances in neural information processing systems, 30, 2017.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble What uncertainties do we need in bayesian deep learning for computer vision? Advances in neural information processing systems, 30, 2017

Reference 49

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Observation c3dafd49-bb60-44ad-b4d6-dab46335ec3a · outbound

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

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 50

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

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Hands-on bayesian neural networks—a tutorial for deep learning users

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.695411Z

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Observation 5c160ab8-8a3a-4196-b25d-641d4e6214e7 · outbound

This paper cites Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational bayesian machine learning.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational bayesian machine learning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.674862Z

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Observation 3795009c-91b8-405e-93d9-74bc2f753b1e · outbound

This paper cites Deep Ensembles: A Loss Landscape Perspective.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Deep Ensembles: A Loss Landscape Perspective

Reference 53

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Observation 5e8824e6-9cb1-4212-8cb5-f26150538a8b · outbound

This paper cites Probabilistic spatiotemporal solar irradiation forecasting using deep ensembles convolutional shared weight long short-term memory network.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Probabilistic spatiotemporal solar irradiation forecasting using deep ensembles convolutional shared weight long short-term memory network

Reference 54

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Observation 24777f37-aab2-4a62-be96-f048d8be2e63 · outbound

This paper cites Obtaining well calibrated probabilities using bayesian binning.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Obtaining well calibrated probabilities using bayesian binning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.068323Z

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Observation f6bc7649-43bf-4022-b7bb-9b62ecfedf2e · outbound

This paper cites On calibration of modern neural networks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble On calibration of modern neural networks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.073597Z

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Observation b54c4da7-0fbb-4f17-80f4-718009bcd018 · outbound

This paper cites Accurate uncertainties for deep learning using calibrated regression.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Accurate uncertainties for deep learning using calibrated regression

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.078393Z

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Observation dee355d5-518d-4460-a0b6-904d734c61da · outbound

This paper cites Evaluating scalable bayesian deep learning methods for robust computer vision.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Evaluating scalable bayesian deep learning methods for robust computer vision

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.564294Z

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Observation 2da44ad7-9849-43da-8c4f-c714d8c55d65 · outbound

This paper cites Evaluating scalable uncertainty estimation methods for deep learning-based molecular property prediction.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Evaluating scalable uncertainty estimation methods for deep learning-based molecular property prediction

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.546779Z

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Observation 2111cbbe-063e-4cf6-b2f9-550e03d7504d · outbound

This paper cites Evaluating and calibrating uncertainty prediction in regression tasks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Evaluating and calibrating uncertainty prediction in regression tasks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.523035Z

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Observation 45d966b2-63b0-48f6-a482-82b5f337d73a · outbound

This paper cites Towards reliable uncertainty quantification via deep ensemble in multi-output regression task.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Towards reliable uncertainty quantification via deep ensemble in multi-output regression task

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.506380Z

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Observation c16c64f7-50f1-4032-a8a8-5982425613d6 · outbound

This paper cites Oscillating-water-column wave energy converters and air turbines: A review.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Oscillating-water-column wave energy converters and air turbines: A review

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.488981Z

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Observation eed96469-e370-409d-98fe-bb0e684f58e4 · outbound

This paper cites Recursive distributed representations.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Recursive distributed representations

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.455901Z

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Observation f96c32c6-b389-4b39-90f5-0666ac16a626 · outbound

This paper cites A general framework for adaptive processing of data structures.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble A general framework for adaptive processing of data structures

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.433406Z

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Observation 7bf16462-d426-4957-bf2a-21add1adb8be · outbound

This paper cites Learning long-term dependencies with gradient descent is difficult.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Learning long-term dependencies with gradient descent is difficult

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.116861Z

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Observation 78a77fee-d574-46bd-b65e-01899a6ab1d8 · outbound

This paper cites Long short-term memory.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Long short-term memory

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.121658Z

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Observation b0eda795-73aa-4972-b483-6c7062d7408a · outbound

This paper cites Learning to forget: Continual prediction with lstm.Neural computation, 12(10):2451–2471, 2000.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Learning to forget: Continual prediction with lstm.Neural computation, 12(10):2451–2471, 2000

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.126411Z

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Observation cbf86427-6938-43c8-b878-bf76df3284d0 · outbound

This paper cites Deep learning, volume 1.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Deep learning, volume 1

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.131372Z

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Observation e03572fe-8224-4621-9378-34c86b60e41c · outbound

This paper cites Practical time series analysis: Prediction with statistics and machine learning.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Practical time series analysis: Prediction with statistics and machine learning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.343336Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4a06cfb4-1931-4a19-a900-4927404fe308 · outbound

This paper cites End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.146193Z

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Observation 11d56cd0-c56a-470a-9111-efbc63caefb5 · outbound

This paper cites Attention-based models for speech recognition.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Attention-based models for speech recognition

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T20:47:09.151379Z

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Observation 0a1be932-3d25-4c3e-9434-7259ac984b8d · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Deepar: Probabilistic forecasting with autoregressive recurrent networks

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.309308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0861370e-01fa-4467-b871-2252b8720be6 · outbound

This paper cites Physics-Constrained Graph Neural Networks for Spatio-Temporal Prediction of Drop Impact on OLED Display Panels.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Physics-Constrained Graph Neural Networks for Spatio-Temporal Prediction of Drop Impact on OLED Display Panels

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:47:09.221287Z

Source-reported events for the cited work

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Observation ca28d315-d6ad-4c9b-b5bf-e0eed46f1b03 · outbound

This paper cites Response of wave energy to tidal currents in the western sea of jeju island, korea.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Response of wave energy to tidal currents in the western sea of jeju island, korea

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.293063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dff681ff-1889-4aee-b198-06d5e9e90310 · outbound

This paper cites Uncertainty quantification and deep ensembles.

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble Uncertainty quantification and deep ensembles

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:47:09.276212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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