Imagen de Portada

GraphFire-X: Physics-Informed Graph Attention Networks and Structural Gradient Boosting for Building-Scale Wildfire Preparedness at the Wildland-Urban Interface

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Esparza, Miguel, Battal, Vamshi, Mostafavi, Ali
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Dynamic Risk Assessment of Wildland-Urban Interface Fires
por: Hu, Yusheng, et al.
Publicado: (2025)

WildfireGenome: Interpretable Machine Learning Reveals Local Drivers of Wildfire Risk and Their Cross-County Variation
por: Liu, Chenyue, et al.
Publicado: (2025)

Characterisation of Hedge Burning in the Context of Wildland Urban Interface (WUI) Fire Prevention
por: Virginie Tihay‐Felicelli, et al.
Publicado: (2025)

Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas
por: Yin, Kai, et al.
Publicado: (2023)

Exploring and Analyzing Wildland Fire Data Via Machine Learning Techniques
por: Dulal, Dipak, et al.
Publicado: (2023)

Hot‐Particle Ignition of Typical Fuels in the Wildland‐Urban Interface and Subsequent Fire Behaviors
por: Kaifeng Wang, et al.
Publicado: (2025)

Progress to Develop Globally Harmonized International Testing Standards for Large Outdoor Fires, Including Wildland‐Urban Interface Fires
por: Samuel L. Manzello
Publicado: (2024)

Automated Wildfire Damage Assessment from Multi view Ground level Imagery Via Vision Language Models
por: Esparza, Miguel, et al.
Publicado: (2025)

Centralized Copy-Paste: Enhanced Data Augmentation Strategy for Wildland Fire Semantic Segmentation
por: Kim, Joon Tai, et al.
Publicado: (2025)

Causal Graph Neural Networks for Wildfire Danger Prediction
por: Zhao, Shan, et al.
Publicado: (2024)

Zoonotic Host Richness in the Global Wildland–Urban Interface
por: Rohan D. Simkin, et al.
Publicado: (2025)

UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate Prediction
por: Xin, Weilin, et al.
Publicado: (2025)

Wildland Fire Smoke in the United States
Publicado: (2022)

Letting People in: Redefining Collaboration in Wildland–Urban Interface Governance
por: Clara Mosso, et al.
Publicado: (2026)

X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation
por: Nabian, Mohammad Amin, et al.
Publicado: (2024)

Path-Based Gradient Boosting for Graph-Level Prediction
por: Meggio, Claudio, et al.
Publicado: (2026)

Explainable Graph Neural Networks Under Fire
por: Li, Zhong, et al.
Publicado: (2024)

Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach
por: Fang, Zhiwei, et al.
Publicado: (2023)

Biological Pathway Informed Models with Graph Attention Networks (GATs)
por: Wong, Gavin, et al.
Publicado: (2025)

Explainable Global Wildfire Prediction Models using Graph Neural Networks
por: Chen, Dayou, et al.
Publicado: (2024)

Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand
por: Chobtham, Kiattikun, et al.
Publicado: (2025)

Dynamic Graph Attention Networks for Travel Time Distribution Prediction in Urban Arterial Roads
por: Yousefzadeh, Nooshin, et al.
Publicado: (2024)

Are Graph Attention Networks Able to Model Structural Information?
por: Noravesh, Farshad, et al.
Publicado: (2025)

STRIDE: Structure and Embedding Distillation with Attention for Graph Neural Networks
por: Ahluwalia, Anshul, et al.
Publicado: (2023)

Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks
por: Park, Eunjeong, et al.
Publicado: (2026)

Flood-DamageSense: Multimodal Mamba with Multitask Learning for Building Flood Damage Assessment using SAR Remote Sensing Imagery
por: Ho, Yu-Hsuan, et al.
Publicado: (2025)

Graph Attention Networks with Physical Constraints for Anomaly Detection
por: Homaei, Mohammadhossein, et al.
Publicado: (2026)

Deep Graph Attention Networks
por: Kato, Jun, et al.
Publicado: (2024)

Learning Structure-from-Motion with Graph Attention Networks
por: Brynte, Lucas, et al.
Publicado: (2023)

Graph-based Integrated Gradients for Explaining Graph Neural Networks
por: Simpson, Lachlan, et al.
Publicado: (2025)

Demystifying Oversmoothing in Attention-Based Graph Neural Networks
por: Wu, Xinyi, et al.
Publicado: (2023)

Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODE
por: Xu, Fan, et al.
Publicado: (2026)

Graph-Based Learning of Spectro-Topographical EEG Representations with Gradient Alignment for Brain-Computer Interfaces
por: Angkan, Prithila, et al.
Publicado: (2025)

GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
por: Wang, Zhixiao, et al.
Publicado: (2026)

Impact of Forest Canopy Structure on Buoyant Plume Dynamics During Wildland Fires
por: Cervantes, Antonio Quim, et al.
Publicado: (2025)

DisasterLex: An Expert Concept-to-Schema Knowledge Graph for Geospatial Reasoning in Disaster Analytics
por: Xiao, Yiming, et al.
Publicado: (2026)

Wildland–Urban Interface Planning: Lessons From a Participatory Mapping Exercise
por: Clara Mosso, et al.
Publicado: (2026)

GraphRAG under Fire
por: Liang, Jiacheng, et al.
Publicado: (2025)

Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
por: Hoang-Minh, Thanh
Publicado: (2025)

WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring
por: Habibpour, Mobin, et al.
Publicado: (2026)