Cover Image

Spatial Modeling and Risk Zoning of Global Extreme Precipitation via Graph Neural Networks and r-Pareto Processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Zimu, Wu, Yifan, Bi, Daning
Format:	Preprint
Published:	2025
Subjects:	Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Boundary-Induced Biases in Climate Networks of Extreme Precipitation and Temperature
by: Ghanbarian, Behzad, et al.
Published: (2026)

Multi-output Extreme Spatial Model for Complex Aircraft Production Systems
by: Lee, Cheolhei, et al.
Published: (2026)

Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
by: Pasche, Olivier C., et al.
Published: (2022)

Quantifying Very Extreme Precipitation and Temperature Using Huge Ensembles Generated by Machine Learning-based Climate Model Emulators
by: Paciorek, Christopher J., et al.
Published: (2025)

Spatial Deep Convolutional Neural Networks
by: Wang, Qi, et al.
Published: (2024)

Likelihood-Free Inference for Multivariate Generalized Pareto Models
by: Aka, Samira, et al.
Published: (2026)

Discovering Spatial Patterns of Readmission Risk Using a Bayesian Competing Risks Model with Spatially Varying Coefficients
by: Shen, Yueming, et al.
Published: (2025)

E-STGCN: Extreme Spatiotemporal Graph Convolutional Networks for Air Quality Forecasting
by: Panja, Madhurima, et al.
Published: (2024)

Observational Study on the District‐Scale Characteristics of Local Precipitation and Extreme Wind From the Tropical Cyclones Affecting Shanghai
by: Zhihui Han, et al.
Published: (2026)

An Analysis of Summer Precipitation Variability and Neural Network‐Based Annual Prediction Over the Northern Part of the Korean Peninsula
by: Yong‐Sik Ham, et al.
Published: (2025)

Spatial Extremes at Scale: A Case Study of Surface Skin Temperature and Heat Risk in the United States
by: Lee, Ben Seiyon, et al.
Published: (2026)

Spatial Process Mining
by: Yoshizawa, Shintaro, et al.
Published: (2025)

Spatial Analysis of Tropical Cyclone Precipitation Through Landfall: A Multi‐Basin Perspective
by: Samrin Sumaiya Sauda, et al.
Published: (2026)

An alternative method of adjusting for multiple comparison in medical research
by: Li, Jiale, et al.
Published: (2025)

Manifold Dimension Estimation via Local Graph Structure
by: Bi, Zelong, et al.
Published: (2025)

Projections of Precipitation and Temperature Changes and Trends Using CMIP6 Global Climate Models in the Eastern Amhara, Northeastern, Ethiopia
by: Mohammed Hussen Kebede, et al.
Published: (2026)

A Composite-Loss Graph Neural Network for the Multivariate Post-Processing of Ensemble Weather Forecasts
by: Lakatos, Mária
Published: (2025)

Recurrent Neural Networks for Multivariate Loss Reserving and Risk Capital Analysis
by: Cai, Pengfei, et al.
Published: (2024)

Anticipating Continued Global Fertility Decline via Neural Forecasting
by: Ciganda, Daniel, et al.
Published: (2026)

Sliced Elastic Distance for Evaluating Amplitude and Phase Differences in Precipitation Models
by: Garrett, Robert C., et al.
Published: (2023)

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions
by: Ling, Jiahe, et al.
Published: (2025)

Correction to “Projections of Precipitation and Temperature Changes and Trends Using CMIP6 Global Climate Models in the Eastern Amhara, Northeastern, Ethiopia”
Published: (2026)

Bayesian Spatial Point Process Modeling for Cluster Randomized Trials
by: Lee, Jooyeon, et al.
Published: (2025)

Thinning-Stable Point Processes as a Model for Spatial Burstiness
by: Zuyev, Sergei
Published: (2025)

Spatially Varying Deep Functional Neural Network: Application in Large-Scale Crop Yield Prediction
by: Park, Yeonjoo, et al.
Published: (2025)

A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting
by: Majumder, Reetam, et al.
Published: (2022)

A Case Study on Quantifying Reliability under Extreme Risk Constraints in Space Missions
by: Sanderson, Dawn L., et al.
Published: (2024)

Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
by: Wang, Qingyi, et al.
Published: (2023)

Kriging Methods for Modelling Spatial Basis Risk in Weather Index Insurances: A Technical Note
by: Guo, Yiping, et al.
Published: (2023)

A Graph Sufficiency Perspective for Neural Networks
by: Shen, Cencheng, et al.
Published: (2025)

Effective Bayesian Modeling of Large Spatiotemporal Count Data Using Autoregressive Gamma Processes
by: Cheng, Yifan, et al.
Published: (2025)

Graph Neural Poisson Models for Supply Chain Relationship Forecasting
by: Xiang, Ling, et al.
Published: (2025)

Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes
by: Sharma, Bharat, et al.
Published: (2025)

Analysis of Spatial Variability and Temporal Trends in the Extreme Rainfall of Kagera Sub‐Basin, Tanzania
by: Nickson Tibangayuka, et al.
Published: (2025)

Resource-Based Time and Cost Prediction in Project Networks: From Statistical Modeling to Graph Neural Networks
by: Mirjalili, Reza, et al.
Published: (2025)

Modeling Spatial Heterogeneity in Exposure Buffers and Risk: A Hierarchical Bayesian Approach
by: Comess, Saskia, et al.
Published: (2025)

Correction to “Can Global Products Capture Precipitation Variability in the Galápagos Islands? An Assessment Based on Climatic Time‐Series Components”
Published: (2025)

Verification of Calibrated Multimodel Subseasonal Precipitation Predictions Cascaded From Global to Regional Scale Over Ceará State in Brazil
by: Caio A. S. Coelho, et al.
Published: (2026)

Integrative Learning of Dynamically Evolving Multiplex Graphs and Nodal Attributes Using Neural Network Gaussian Processes with an Application to Dynamic Terrorism Graphs
by: Rodriguez-Acosta, Jose, et al.
Published: (2026)

Sustainable Greenhouse Microclimate Modeling: A Comparative Analysis of Recurrent and Graph Neural Networks
by: Seri, Emiliano, et al.
Published: (2025)