Copertina

The Merit of River Network Topology for Neural Flood Forecasting

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kirschstein, Nikolas, Sun, Yixuan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting
di: Eddin, Mohamad Hakam Shams, et al.
Pubblicazione: (2025)

Decision-focused Sensing and Forecasting for Adaptive and Rapid Flood Response: An Implicit Learning Approach
di: Sun, Qian, et al.
Pubblicazione: (2025)

Global River Forecasting with a Topology-Informed AI Foundation Model
di: Ren, Hancheng, et al.
Pubblicazione: (2026)

Short-term Streamflow and Flood Forecasting based on Graph Convolutional Recurrent Neural Network and Residual Error Learning
di: Pan, Xiyu, et al.
Pubblicazione: (2024)

FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation
di: Shi, Jimeng, et al.
Pubblicazione: (2024)

Shared-Weights Extender and Gradient Voting for Neural Network Expansion
di: Chatzis, Nikolas, et al.
Pubblicazione: (2025)

Implementing a GRU Neural Network for Flood Prediction in Ashland City, Tennessee
di: Fordjour, George K., et al.
Pubblicazione: (2024)

Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting
di: Mercier, Valentin, et al.
Pubblicazione: (2026)

Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits
di: Wang, Jiachen T., et al.
Pubblicazione: (2024)

DUALFloodGNN: Physics-informed Graph Neural Network for Operational Flood Modeling
di: Acosta, Carlo Malapad, et al.
Pubblicazione: (2025)

Probabilistic Demand Forecasting with Graph Neural Networks
di: Kozodoi, Nikita, et al.
Pubblicazione: (2024)

Graph Neural Networks for Electricity Load Forecasting
di: Campagne, Eloi, et al.
Pubblicazione: (2025)

Simple Feedfoward Neural Networks are Almost All You Need for Time Series Forecasting
di: Sun, Fan-Keng, et al.
Pubblicazione: (2025)

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data
di: Xiong, Weijiang, et al.
Pubblicazione: (2025)

ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
di: Cai, Wanlin, et al.
Pubblicazione: (2024)

Merit-based Fair Combinatorial Semi-Bandit with Unrestricted Feedback Delays
di: Chen, Ziqun, et al.
Pubblicazione: (2024)

Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting
di: Xiong, Weijiang, et al.
Pubblicazione: (2026)

Accelerating HEC-RAS: A Recurrent Neural Operator for Rapid River Forecasting
di: Holmberg, Edward, et al.
Pubblicazione: (2025)

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
di: Oskarsson, Joel, et al.
Pubblicazione: (2024)

SF$^2$Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida
di: Zheng, Xu, et al.
Pubblicazione: (2025)

Predicting Mechanical Properties from Microstructure Images in Fiber-reinforced Polymers using Convolutional Neural Networks
di: Sun, Yixuan, et al.
Pubblicazione: (2020)

Fine Flood Forecasts: Incorporating local data into global models through fine-tuning
di: Ryd, Emil, et al.
Pubblicazione: (2025)

Conditional Uncertainty Quantification for Tensorized Topological Neural Networks
di: Wu, Yujia, et al.
Pubblicazione: (2024)

Topological Neural Networks go Persistent, Equivariant, and Continuous
di: Verma, Yogesh, et al.
Pubblicazione: (2024)

On the Topology Awareness and Generalization Performance of Graph Neural Networks
di: Su, Junwei, et al.
Pubblicazione: (2024)

Exploring Topological Bias in Heterogeneous Graph Neural Networks
di: Zhang, Yihan
Pubblicazione: (2025)

Ontology Neural Networks for Topologically Conditioned Constraint Satisfaction
di: Oh, Jaehong
Pubblicazione: (2026)

Topology of Out-of-Distribution Examples in Deep Neural Networks
di: Datta, Esha, et al.
Pubblicazione: (2025)

Topological Feature Compression for Molecular Graph Neural Networks
di: Khorana, Rahul
Pubblicazione: (2025)

APS-LSTM: Exploiting Multi-Periodicity and Diverse Spatial Dependencies for Flood Forecasting
di: Feng, Jun, et al.
Pubblicazione: (2024)

Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networks
di: Papillon, Mathilde, et al.
Pubblicazione: (2023)

On the Topology of Neural Network Superlevel Sets
di: Gharesifard, Bahman
Pubblicazione: (2026)

Topological Neural Networks over the Air
di: Fiorellino, Simone, et al.
Pubblicazione: (2025)

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
di: Lee, Sanghyun, et al.
Pubblicazione: (2024)

Progressive Neural Network for Multi-Horizon Time Series Forecasting
di: Lin, Yang
Pubblicazione: (2023)

Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall
di: Bülte, Christopher, et al.
Pubblicazione: (2025)

Recurrent Neural Networks with Linear Structures for Electricity Price Forecasting
di: Amor, Souhir Ben, et al.
Pubblicazione: (2025)

From GARCH to Neural Network for Volatility Forecast
di: Zhao, Pengfei, et al.
Pubblicazione: (2024)

Graph Neural Networks in Wind Power Forecasting
di: Castellano, Javier, et al.
Pubblicazione: (2025)