Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation | Paper Citation Record

Observation 7cd1df3f-0315-4cea-98b0-a56bd1e2a251 · outbound

This paper cites Effective management of class imbalance problem in climate data analysis using a hybrid of deep learning and data level sampling.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Effective management of class imbalance problem in climate data analysis using a hybrid of deep learning and data level sampling

Reference 1

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This paper cites Self-clustered gan for precipitation nowcasting.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Self-clustered gan for precipitation nowcasting

Reference 2

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This paper cites The rise of data-driven weather fore- casting: A first statistical assessment of machine learning– based weather forecasts in an operational-like context.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation The rise of data-driven weather fore- casting: A first statistical assessment of machine learning– based weather forecasts in an operational-like context

Reference 3

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Observation 2262fa4b-f6b5-48f1-821b-dcb3b641f964 · outbound

This paper cites Big data in precision agriculture: Weather forecasting for future farming.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Big data in precision agriculture: Weather forecasting for future farming

Reference 4

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Observation 7cb76c3a-d9f1-46ea-b502-bde7f9c631fe · outbound

This paper cites Addressing class imbalance in deep learning for small lesion detection on medical images.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Addressing class imbalance in deep learning for small lesion detection on medical images

Reference 5

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Observation eeec61d3-4130-4101-8f62-10f4fb390747 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Swin-unet: Unet-like pure transformer for medical image segmentation

Reference 6

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Observation 06458606-b51f-4abe-86ee-c55309a1ce50 · outbound

This paper cites Pcct: Progressive class-center triplet loss for imbalanced medical image classification.IEEE Jour- nal of Biomedical and Health Informatics, 27(4):2026–2036,.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Pcct: Progressive class-center triplet loss for imbalanced medical image classification.IEEE Jour- nal of Biomedical and Health Informatics, 27(4):2026–2036,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.411459Z

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Observation a231602b-1bb4-4ac3-94c3-4582bb1eb817 · outbound

This paper cites Contribution of historical precipitation change to us flood damages.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Contribution of historical precipitation change to us flood damages

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.395754Z

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Observation 3e78ea6e-a844-40f2-ae59-365fd39d3fbe · outbound

This paper cites Machine learning for numerical weather and climate mod- elling: a review.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Machine learning for numerical weather and climate mod- elling: a review

Reference 9

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Observation 15e8b761-6cba-4964-bac3-2194bac6e149 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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Observation 11a4e2e9-0077-47a1-8871-64800e008358 · outbound

This paper cites Multiscale vision transformers.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Multiscale vision transformers

Reference 11

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Observation 4a6ba44a-6122-48cc-a302-1737fcc60dd0 · outbound

This paper cites Masked autoencoders as spatiotemporal learners.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Masked autoencoders as spatiotemporal learners

Reference 12

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Observation 6e8ecad6-0fbf-433c-90f6-358a3c77defb · outbound

This paper cites Han- dling imbalanced medical image data: A deep-learning- based one-class classification approach.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Han- dling imbalanced medical image data: A deep-learning- based one-class classification approach

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.335938Z

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Observation 8a649059-5242-44ee-8c1a-41d3f426deac · outbound

This paper cites Spatio-temporal enhanced contrastive and contextual learning for weather forecasting.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Spatio-temporal enhanced contrastive and contextual learning for weather forecasting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.319504Z

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Observation 30af01ab-3d7c-4ff3-85fa-fdc98f0fd846 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Masked autoencoders are scalable vision learners

Reference 15

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Observation 515287d6-18f5-418f-aa75-bcf874445ef0 · outbound

This paper cites Deep learning for improving numerical weather prediction of heavy rain- fall.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Deep learning for improving numerical weather prediction of heavy rain- fall

Reference 16

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Observation 978254f5-95a4-43c7-8004-784c7dae1841 · outbound

This paper cites Survey on deep learning with class imbalance.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Survey on deep learning with class imbalance

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.277709Z

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Observation 02fcc587-8111-4fef-ba55-b7fe9b29f094 · outbound

This paper cites Decoupling Representation and Classifier for Long-Tailed Recognition.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Decoupling Representation and Classifier for Long-Tailed Recognition

Reference 18

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Observation 4ef775a3-44f2-48b2-968c-9df675abd0c6 · outbound

This paper cites Forecasting Global Weather with Graph Neural Networks.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Forecasting Global Weather with Graph Neural Networks

Reference 19

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Observation 0131f0eb-ae0c-4abc-9f86-5acd05d57012 · outbound

This paper cites Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction

Reference 20

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Observation dcadfc42-2e28-41ba-807d-4e333d2f2f7e · outbound

This paper cites Validation of integrated multisatellite retrievals for gpm (imerg) by us- ing gauge-based analysis products of daily precipitation over east asia.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Validation of integrated multisatellite retrievals for gpm (imerg) by us- ing gauge-based analysis products of daily precipitation over east asia

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.262283Z

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Observation 5ac5268e-742d-4f3f-9d30-d6c71b3b14b2 · outbound

This paper cites Real-world data: a brief review of the methods, applications, challenges and opportunities.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Real-world data: a brief review of the methods, applications, challenges and opportunities

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.246436Z

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Observation de0c3ca3-3ee9-4f0b-8f6b-e85dedccd767 · outbound

This paper cites Deep-learning post-processing of short-term station precipitation based on nwp forecasts.Atmospheric Research, 295:107032, 2023.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Deep-learning post-processing of short-term station precipitation based on nwp forecasts.Atmospheric Research, 295:107032, 2023

Reference 24

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Observation 02a367bc-0dfb-4423-b7b6-707f601cb96d · outbound

This paper cites Exploring the limits of weakly supervised pretraining.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Exploring the limits of weakly supervised pretraining

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.213436Z

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Observation eb8f9f80-2910-4810-a6cd-9326aeef7b9a · outbound

This paper cites W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting

Reference 26

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Observation a041987b-4f0a-498b-864c-622196617428 · outbound

This paper cites Self-supervised rep- resentation learning from 12-lead ecg data.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Self-supervised rep- resentation learning from 12-lead ecg data

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.196220Z

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Observation 7fcfe901-3bae-47ee-a932-31a66326019c · outbound

This paper cites When does label smoothing help? Advances in neural in- formation processing systems, 32, 2019.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation When does label smoothing help? Advances in neural in- formation processing systems, 32, 2019

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.180405Z

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Observation 4d870aec-d2ad-4f79-ae04-563ef415bcd8 · outbound

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

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 29

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Observation 307478b8-4d49-4e4b-85d1-9cefd95b11a8 · outbound

This paper cites Deep learning models for generation of precipitation maps based on numerical weather prediction.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Deep learning models for generation of precipitation maps based on numerical weather prediction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.163899Z

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This paper cites Post- processing of nwp precipitation forecasts using deep learn- ing.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Post- processing of nwp precipitation forecasts using deep learn- ing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.146257Z

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Observation 6730a898-1dd0-4e08-a965-cf86b26409e6 · outbound

This paper cites Spatio- temporal downscaling of climate data using convolutional and error-predicting neural networks.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Spatio- temporal downscaling of climate data using convolutional and error-predicting neural networks

Reference 32

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Observation 8293ea21-3822-4e99-bc17-409ea4ff753f · outbound

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

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Convolutional lstm network: A machine learning approach for precipitation nowcasting

Reference 33

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Observation 8d897315-d2f4-4d70-b750-0ce3a1e180ce · outbound

This paper cites Simplifying neural network training under class imbalance.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Simplifying neural network training under class imbalance

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.095763Z

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Observation 374a4bca-689f-45fb-bcfe-e7bd424681db · outbound

This paper cites Environmental hazards: assessing risk and re- ducing disaster.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Environmental hazards: assessing risk and re- ducing disaster

Reference 35

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Observation ec0d52d0-a04e-4bee-88ab-ac191155d9c7 · outbound

This paper cites MetNet: A Neural Weather Model for Precipitation Forecasting.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation MetNet: A Neural Weather Model for Precipitation Forecasting

Reference 36

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This paper cites PostRainBench: A comprehensive benchmark and a new model for precipitation forecasting.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation PostRainBench: A comprehensive benchmark and a new model for precipitation forecasting

Reference 38

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This paper cites Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.061914Z

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Observation 01da277a-f93d-4a62-b4aa-32229e6b5451 · outbound

This paper cites Exploiting domain knowledge to address class imbalance in meteoro- logical data mining.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Exploiting domain knowledge to address class imbalance in meteoro- logical data mining

Reference 40

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Observation 6a115255-885b-4d2b-9f73-52a952819ce1 · outbound

This paper cites Attention is all you need.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Attention is all you need

Reference 41

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This paper cites Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.017754Z

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Observation 58307d81-196d-41bb-b205-8becf3f9daba · outbound

This paper cites Long-tailed Recognition by Routing Diverse Distribution-Aware Experts.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Long-tailed Recognition by Routing Diverse Distribution-Aware Experts

Reference 43

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This paper cites Guide to meteorolog- ical instruments and methods of observation.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Guide to meteorolog- ical instruments and methods of observation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:14.001374Z

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This paper cites Unified perceptual parsing for scene understand- ing.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Unified perceptual parsing for scene understand- ing

Reference 45

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This paper cites mixup: Beyond Empirical Risk Minimization.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation mixup: Beyond Empirical Risk Minimization

Reference 46

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This paper cites Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

Reference 47

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This paper cites Leave no stone unturned: Mine extra knowledge for imbal- anced facial expression recognition.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Leave no stone unturned: Mine extra knowledge for imbal- anced facial expression recognition

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:25:13.958916Z

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This paper cites Ur- ban computing: concepts, methodologies, and applications.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Ur- ban computing: concepts, methodologies, and applications

Reference 49

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This paper cites an unresolved cited work.

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation Unresolved cited work

Reference 2008

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